User interface for search method and system

ABSTRACT

A computer-implemented method is provided. The method comprises causing presentation of a graphical user interface (GUI) on a screen, the GUI including a first option that enables specifying a value for a category of a plurality of categories associated with a property, a second option that enables specifying a weight for the category, and a map; receiving a certain value for the category via the first option and a certain weight for the category via the second option; computing a relevance value for each of a plurality of properties based on the certain value and the certain weight, the certain value and the certain weight in combination determining an amount of contribution of the category to the relevance value for the property, including when the property does not match the certain value in the category; and causing the map to include a list of visual indicators for one or more properties of the plurality properties based on locations of the plurality of properties and relevance values computed for the plurality of properties.

RELATED APPLICATIONS

This application claims the benefit under 35 U.S.C. § 120 as acontinuation of U.S. patent application Ser. No. 14/283,659, filed May21, 2014, which is a continuation of U.S. patent application Ser. No.12/120,114, filed May 13, 2008, which is a continuation-in-part of U.S.patent application Ser. No. 10/534,627, filed Jan. 3, 2006, now U.S.Pat. No. 7,461,051 issued Dec. 2, 2008, which is a national stage entryof PCT/US2003/036045, filed Nov. 10, 2003, which claims the benefitunder 35 U.S.C. 119(e) of U.S. Provisional Patent Application60/425,361, filed Nov. 11, 2002, the entire contents of which are herebyincorporated by reference for all purposes as if fully set forth herein.Applicant hereby rescinds any disclaimer of claim scope in the parentapplications or the prosecution history thereof and advise the USPTOthat the claims in this application may be broader than any claim in theparent applications.

FIELD OF THE INVENTION

The present invention relates generally to a user interface for asearching method and system.

BACKGROUND OF THE INVENTION

The Internet, and particularly the Worldwide Web, has caused a virtualinformation explosion. An average user, making use of a conventional webbrowser, now has available to him a mass of information that would havebeen unimaginable just a few years ago. This includes informationavailable from professional and commercial sources, individuals, andmessage boards or forums, where users “congregate” to discuss everyimaginable topic, and some that are not. With the wealth of informationthat is available, a new problem has arisen: How can that information befound?

This problem has been addressed by a plethora of “search engines”, whichare software programs and information systems that are specificallydesigned to assist users in finding information. While existing searchengines have been adequate, they are limited in their ability to uncoveruseful information when users are searching. The primary reason is thatsearch engines tend to be language based, and a searcher is not alwaysfamiliar with the common terminology in his field of search. Also, theremay be useful information available which does not conform to the commonterminology. It also takes substantial skill or experience to formulatequeries that will produce meaningful results.

In accordance with the present invention, search results are achievedthat are broader and more intelligent than basic keyword searching. Thisis achieved by imposing a structure on data being searched and utilizingthe same structure for search queries. Relevant information is thenuncovered by correlating the structure of the data being searched andthe structure of the query. Items to be searched can include anything:messages, discussions, articles, polls, transcripts, or anything elsethat can be linked to or pulled from a database. Search results can beincluded that are less than 100% relevant, and not just 100% relevant.In the absence of, or in addition to, results that would be generated bya Boolean keyword-only-search, users can retrieve results of somerelevance, for example as determined by a set of selectable filtercriteria. Consequently, merchants can sell inventory which mightotherwise be unseen and/or users can find information which mightotherwise stay hidden in an overly strict Boolean search.

The method of the present invention is the glue that holds onlinespeakers together as they seek to use the Worldwide Web to communicateas they do in life. It lets users speak without seeing the spam thatfills most message boards; allows interesting conversations to takeplace without interruption; and gives users the anonymity to talkcandidly without fear that their identities may be revealed.

Where message board sites or forums are concerned, the present inventiontransforms ordinary sites into profitable “para-sites.” Para-sites aresites that feed off the work of their own users. A para-site powered bythe present invention collects interesting, relevant information byharnessing users to post and organize content, at no cost to thesite-operator. Methods and systems embodying the present invention willhereafter be referred to by use of the assignee's trademarkTRANSPARENSEE™. Users find sites stickier than other sites because ofthe high quality of information generated by the present invention. Siteowners can restrict access to this information in different ways,allowing the most valuable information to be repackaged and resold todifferent markets at different price points.

As repositories of filtered information, TRANSPARENSEE™ sites attractusers with specific interests. Users who speak intelligently aboutsubjects they know soon find that their opinions on that subject carrymore weight—and are heard by more people—than the opinions of others.The weight given to a particular user's thoughts on a subject isquantified as the user's “reputation” for knowing that subject.

TRANSPARENSEE™ sites allow users to develop and maintain complex,multi-variable reputations for a wide variety of different subjects. Asusers develop high reputations for knowing a particular subject, theygain privileges on the site as a result; as they gain privileges, theirinvestment in the site grows. High-reputation users become reluctant tomove conversations off-site because, by leaving, they'll lose thebenefits they've gained as high-reputation users.

As a result, high-reputation users tend to remain on TRANSPARENSEE™sites, and communities develop. These communities are deeply rooted inthe site due to the investments their members have made by buildingreputations. For this reason, community members (and communities) cannoteasily be lured away to non-TRANSPARENSEE™ sites.

A sticky community of experts sharing information in a highly accessibleway attracts new users. New users generate content, develop reputations,and become community members, thus adding to the attractive pull of thecommunity.

These network effects feed upon themselves, building small communitiesinto large ones. The larger a community grows, the more information ithas under discussion, the greater the number and expertise of its users,and the stronger a pull it exerts on new members. When a community growslarge enough and vibrant enough, it becomes the only logical place for anew user to go in order to learn about or discuss a subject.

Because the present invention makes it easier for people to communicate,sites that use the present invention quickly attract users. As theseusers gain reputations they develop into communities that are hard todisplace. Network effects cause these communities to grow quickly. Takentogether, this means that the first company to use the reputationfeature of the present invention in any particular market has asubstantial first-mover advantage. The bulk of users in that market willend up on TRANSPARENSEE™ sites, and will form deep-rooted communities

TRANSPARENSEE™ site reputations are portable. Reputation values arestored at and administered from a central location, allowing users tocarry their reputations with them from TRANSPARENSEE™ site toTRANSPARENSEE™ site. In other embodiments, reputation values are storedin a partly or wholly distributed fashion.

As the number of TRANSPARENSEE™ sites grows, the company's proprietarydatabase of reputations also grows. When this database has reached acritical mass it will have tremendous value. Companies that choose topower their sites with the present invention will automatically becomemembers of the TRANSPARENSEE™ Network, allowing them access to a largeuser base of individuals who may start using their pre-built reputationson the new site right away.

By allowing Web-site operators to inexpensively gather and distribute“insider speech,” the present invention fills a demand which, thoughstrong, has not been met by any other product. The invention is equallyunique in the way that it allows licensees to precisely target usersbased on detailed information without invading their individual privacy.

The present invention provides several immediate benefits. It promotesthe disclosure of superior information, then ranks and organizes thatinformation in a way that allows it to be easily packaged and sold todifferent audiences at different price points. It makes sites stickierwhile at the same time allowing licensees to provide advertisers withfar more narrowly targeted advertisements than they otherwise could,substantially increasing advertising revenues. And it allows companiesto lessen (or eliminate) the cost of hiring moderators to monitor onlinediscussion.

SUMMARY OF THE INVENTION

A user interface is provided herein for receiving a search query for adatabase stored in computer storage, the database having multiplerecords. Each record may contain information regarding one or morecategories, each category having an assigned weight value. The searchquery may comprise a set of one or more search criteria of one or morecategories for searching the database. The user interface may provide acategory-weight slider tool associated with a category, thecategory-weight slider tool for receiving changes in a weight value ofthe associated category from a user. The user interface may also providea search-results section for displaying one or more exact matchingrecords and one or more non-exact matching records, each exact matchingrecord comprising information that exactly matches received searchcriteria and each non-exact matching record comprising information thatdoes not exactly match one or more received search criteria.

Each non-exact matching record may have a relevance value representingthe relevance of the non-exact matching record to the search query, arelevance value for a record being based, in part, on weight valuesassociated with the one or more categories. The non-exact matchingrecords may be displayed in the search-results section in an orderingbased on the relevance values. Upon the category-weight slider toolreceiving a new weight value of a category from the user, a new orderingof the non-exact matching records is displayed based on the new weightvalue. The user interface may display the new orderings of the non-exactmatching records dynamically and in real-time as new weight values arereceived from the category-weight slider tool without requiring the userto type in new weight values or to otherwise initiate displaying the neworderings.

The user interface may further provide a category-value slider toolassociated with a category, the category-value slider tool for receivingchanges in search criterion of the associated category from a user. Uponthe category-value slider tool receiving a new search criterion of acategory from the user, the search-results section displays (dynamicallyand in real-time) a new ordering of the non-exact matching records basedon the new search criterion. The user interface may further provide amapping tool for determining address information contained in the searchresults and displaying symbols representing the search results on a map.Upon the category-weight slider tool receiving a new weight value or newsearch criteria of a category from the user, symbols representing newsearch results are displayed based on the new weight value and/or newsearch criteria. The user interface may further provide a search-resultselection function for receiving a user selection of a search result.Upon receiving a selection of a search result, the function uses theinformation of the selected search result as search criteria for a newsearch query, and displays search results based on the new search query.

In some embodiments, the user interface provides a category-value slidertool associated with a category and a drill down tool for an associatedsearch criterion of an associated category. The drill down tool maydisplay an exact-match number comprising the number of recordscomprising information that exactly matches the search criterionassociated with the drill down tool and all received search criteria.Upon the category-value slider tool receiving a new search criterion ofa category from the user, the drill down tool may display a newexact-match number based on the new search criterion. The drill downtool may display new exact-match numbers dynamically and in real-time asnew search criteria are received from the category-value slider toolwithout requiring the user to type in new search criteria or tootherwise initiate displaying of the new exact-match numbers. The userinterface may further provide a multi-select drill-down function forallowing simultaneous selection of two or more search criteria(associated with the two or more drill down tools) specified for thesame category.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing brief description, as well as further objects, features,and advantages of the present invention will be understood morecompletely from the following detailed description of a presentlypreferred, but nonetheless illustrative embodiment, with reference beinghad to the accompanying drawings, in which:

FIG. 1 illustrates an embodiment of a typical static system whereinboards are grouped by firms, industries and topics;

FIG. 2 illustrates one embodiment of a system running utilizing thereputation aspect of the present invention;

FIG. 3 illustrates examples of relationships;

FIG. 4 illustrates an embodiment of a simple dynamic system;

FIG. 5 illustrates an example of selected categories of content and userselected categories being used as inputs to generate relevances;

FIG. 6 illustrates an embodiment of a complex dynamic system;

FIG. 7 illustrates an example flow chart for updating a user's rating;

FIG. 8 shows an example of calculating an aggregate reputation;

FIG. 9 illustrates an embodiment of threshold filtering wherein apalette contains a scatterplot. And each dot represents s message;

FIG. 10 illustrates an embodiment of a scatterplot wherein the user haschosen to view messages of high message quality without much regard tothe reputation of the poster;

FIG. 11 illustrates an embodiment of a scatterplot wherein the user haschosen to view messages posted by users with high reputations withoutmuch regard to message quality;

FIG. 12 illustrates an embodiment of a scatterplot wherein the user haschosen to view messages of high quality written by people with highreputations;

FIG. 13 illustrates an embodiment of a scatterplot wherein the averagecombination of reputation and message rating is selected by users of acertain filter set;

FIG. 14 illustrates an embodiment of related filters;

FIG. 15 illustrates an example flow chart of annotation posting;

FIG. 16 illustrates an embodiment of tagged content;

FIG. 17 illustrates an embodiment of annotated tagged content;

FIG. 18 illustrates an example flow chart of posting at different levelsof anonymity;

FIG. 19 illustrates key features of different levels of anonymity;

FIG. 20 illustrates an example of onion routing;

FIG. 21 illustrates an example of determining a discussion rating basedon multiple factors;

FIG. 22 is a functional block diagram illustrating the preferredenvironment for the present invention;

FIG. 23 is an exemplary partial screen shot presented to a searcher inthe dating service database;

FIG. 24 is a screen shot representing the results of an exemplarysearch;

FIGS. 25a and 25b , together illustrate the results of an enhancedsearch;

FIGS. 26a and 26b are screen shots of a page of the online datingservice which permits a searcher to review a candidate's long answersand a summary of the multiple choice answers;

FIG. 27 is a screen shot of a summary page for a user;

FIG. 28 is a multi-level tree representing a category with ahierarchical structure;

FIG. 29 illustrates a scalar category as represented by a tree with asingle top node;

FIG. 30 is a tree diagram illustrating a process for determiningrelevance of a category having a hierarchical data structure;

FIG. 31 is a tree diagram illustrating a process for determining therelevance value of a category having a scalar structure;

FIG. 32 shows an exemplary screen shot of a user interface for selectinginitial search criteria in a real estate service;

FIGS. 33A-B show exemplary screen shots of user interfaces implementingcategory-weight slider tools;

FIGS. 34A-B show exemplary screen shots of user interfaces implementinguser selectable category-value slider tools;

FIGS. 35A-B show exemplary screen shots of user interfaces implementinga mapping tool;

FIGS. 36A-F show exemplary screen shots of user interfaces implementingdrill down tools;

FIGS. 37A-B show exemplary screen shots of user interfaces implementingcategory-value slider tools for use in conjunction with drill downtools;

FIGS. 38A-B show exemplary screen shots of user interfaces providing thesearch-result selection function for selecting a particular searchresult as search criteria for a new search; and

FIG. 39 shows an exemplary screen shot of a user interface implementingvarious user interface tools and functions described herein.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The disclosure of United States Patent Application entitled “SEARCHMETHOD AND SYSTEM AND SYSTEM USING THE SAME,” having Ser. No. 10/534,627filed on Jan. 3, 2006, is expressly incorporated herein by reference.

FIG. 22 is a functional block diagram illustrating the preferredenvironment for the present invention. A plurality of users' computers Uaccess a content server C via a network I, preferably the Internet.Server C provides the users U access to a content database CD. DatabaseCD may provide various types of information. For example, it maymaintain the information used by an online dating service.Alternatively, it could provide the information for a restaurant surveyservice or wine survey service, or numerous other special interestservices. Database CD could also include, in addition to surveys,product reviews and articles of interest on various subjects.

Also connected to the network I is a web server W which cooperates witha system S, in accordance with the present invention, to manage users'access to information in database CD. Within system S, a query andsearch module 20 in accordance with the present invention interfaceswith users, permitting them to formulate requests for information fromdatabase CD. Module 20 creates, manages and maintains a structuredatabase 10, which contains information describing the structuralrelationship between various pieces of information in database CD.Database 10 also contains information relating to the structuralrelationship between various portions of information in a query in aformat comparable to the structural relationship of information indatabase CD.

In accordance with the present information, information in the database10 is used to correlate the data structure of a query to the structureof database CD, in order to determine that information in database CDwhich needs to be provided to a user in response to a query. Server Wthen connects the user to server C, with instructions to server Cregarding what information is to be provided to the user from databaseCD.

In some embodiments of the invention, system S also includes a userinformation module. This module is particularly useful in systems inwhich users access information in database CD which has been provided byother users. Module 30 could then, for example, include informationabout the reputation of various users with respect to the informationwhich they have furnished. A user accessing information in database CDwhich has been provided by other users is then able to gauge thereliability of that information.

Those skilled in the art will appreciate that the functions of servers Cand W could be combined in a single server. Alternatively, server W andsystem S could accommodate access to different, independent contentdatabases CD relating to different subject matter. The user couldthereby be offered access to information in a plurality of databases ofdifferent content through a single query generated via web server W.

The invention will best be understood through the detailed descriptionof a number of preferred embodiments. In accordance with a firstembodiment, a dating service is provided in which persons seekingpotential mates (candidates) populate a database with informationrelating to themselves. Potential mates (searchers) can then access thatdatabase, providing various search criteria, in order to locateappropriate, potential mates. Those skilled in the art will appreciatethat a similar model is applicable for numerous other services, such as,employment agency services.

FIG. 23 is an exemplary screen shot presented to a searcher in thedating service database. The searcher is presented with a plurality ofmultiple choice menus 40 from which he is to select desirable traits ofa potential mate. For example, the top three menus on the left of FIG.23 relate to the gender, height and weight of a potential mate, whilethe top three menus 40 on the right relate to the age, marital statusand education of the potential mate. A searcher need not make aselection in every menu 40, but only those which he considers important.Upon making those selections, the searcher clicks on the search button42, and the search commences. Although not shown specifically on thisscreen, the searcher may be offered an opportunity to assign a relativeweight to the different menus prior to activating the search.

FIG. 24 is a screen shot representing the results of an exemplarysearch. In this case, the user has made selections in menus 40 relatingto gender, age, height, martial status, weight, education, eye color,and hair color. That search has produced two candidates, Heidildtch andBobou, both of which are exact matches to the selected criteria.

In this embodiment, a searcher is also able to click on the button 44 inorder to obtain an enhanced search.

FIGS. 25a and 25b , together illustrate the results of an enhancedsearch. In addition to the two exact matches, there are a number ofapproximate matches. For example, “Landdecker” has a weight in excess ofthe selected category, but otherwise matches. Similarly, starting with“Helena”, the weight is below the selected range. Similarly, theremaining entries in FIG. 25a all relates to weight which are in excessof the selection and FIG. 25b relates to candidates which are older. Thepresent invention is therefore able to locate matches which are close,but are not exact. The candidates are listed in decreasing order ofrelevance as defined by the user's selected criteria. The listing ofusers with different weights above those which are older reflects arelative higher menu weighting imposed on the weight sub-category thanon the age sub-category.

In accordance with the present embodiment, a candidate also provideslong answers to preset questions. FIGS. 26a and 26b are screen shots ofa page of the online dating service which permits a searcher to review acandidate's long answers (FIG. 26a ) and a summary of the multiplechoice answers (FIG. 26b ). In the column 50 of FIG. 26a , the searcheris also offered a list of the candidates most similar to this one. Atthis point, the searcher may click on any of the other candidates incolumn 50, and he will be able to access the data for that candidate.

For example, should the user click “LubaO” in column 50, he would betransferred to a summary page for that user, illustrated by the screenshot of FIG. 27.

As explained above, the present invention is not limited to textsearching, but can find relevant information even when text does notmatch. This is accomplished by establishing the relevance of data basedupon correlating a searcher's selected data with the data structure ofdatabase 10. In order to achieve this, database 10 must containinformation representing the structural relationship of information indatabase CD, and that information must be updated as the content ofdatabase CD is changed.

In creating database 10, it is first necessary to define categories ofinformation in database CD. For example, in the database represented bythe screen of FIG. 23, each of menus 40 could represent a separatecategory. In FIG. 23, each of the categories is “scalar”, in that thereare a set of unique selections without subcategories. It is alsopossible to have a “dual scalar” or two-dimensional scalar category. Forexample, a geographical database might have longitude and latitude.Triple or higher order scalar categories are also possible (e.g., ageographical database could include altitude).

Another structure for categories might be a “hierarchical” structure.This structure has the form of a tree. For example, the dating databasecould include a category for religion. That category could include afirst level of subcategories, such as Christian, Jewish, and Moslem.Each of these religions would then be divided into furthersubcategories.

For example, the Christian category could be sub-divided into Catholicand Protestant, with each of those being further subdivided intodifferent sects.

In accordance with the present invention, it has been found that bettersearch results can be obtained by using a correlation procedure which isdifferent for different types of data structures. In creating thestructure database 10, each record (e.g., the information relating to asingle candidate) would be parsed into categories, and the database 10would retain information regarding the structure of each category.Thereafter, in determining the relevance of a particular record, thesearcher's selections in each category would be correlated to thestructure of that category in order to arrive at a value representingthe relevance of that category. All of the categories in the recordwould then be processed, for example, by averaging, in order to arriveat a quantity representing the relevance of the record. In this manner,a relevance value is obtained for each record.

As an aid to understanding the relevance determination process, it isconvenient to characterize categories in terms of a tree structure. Forexample, a character with a hierarchical structure could be representedas a multi-level tree as illustrated in FIG. 28. Here, the category isrepresented by the top node 60, while the sub-categories are representedby the nodes 62 a-62 b, and the level of information below that isrepresented by the nodes 64 a-64 d. Similarly, as illustrated in FIG.29, a scalar category could be represented by a tree with a single topnode, 70, representing the category and one secondary level of nodes 72a-72 e representing the sub-categories. Other forms of data structuresare possible and could be similarly represented by a tree structure withnodes. However, those skilled in the art will appreciate that theinvention is not limited to categories and sub-categories that can berepresented by a tree structure. For example, the concepts of theinvention are equally applicable to data structures that can berepresented as a set of scalar values. In the dating site example, asearcher might designate his address by latitude and longitude (orstreet and avenue) in order to locate dating candidates within a certaindistance. The structure of this date is a multi-dimensional vector.

FIG. 30 illustrates the process for determining relevance of a categoryhaving a hierarchical data structure. This involves generating aselection tree TS and a data structure tree TD. In each tree,corresponding nodes are similarly numbered. This is only necessary toassure consistent treatment of corresponding nodes so that the numberingmay be somewhat arbitrary. In the selection tree TS each node has abinary weighting next to it. A node which is selected by the searcher isgiven a weight of 1 and a node which is not selected is given a weightof 0. In the data structure tree, node weights are assigned starting atthe lowest level nodes, which are assigned a weight of 1.0, anddecreasing weights are assigned to each successively higher level ofnodes. It is presently preferred that each successively higher level ofnode be provided a weight which is 90% of the weight of the next lowerlevel node. Thus, nodes at the second level from the bottom are assigneda weight of 0.9, nodes at the third level from the bottom, are assigneda weight of 0.81, and so forth. In order to obtain a relevance value forthe category represented by these trees, corresponding nodes weightvalues are correlated to arrive at a category relevance value. It ispresently preferred that for a hierarchical data structure, the wellknown cosine coefficient algorithm be used for relevancy determination.That algorithm could be represented by the equation 1:

$\begin{matrix}{{R_{A}\left( {S,D} \right)} = \frac{\sum\limits_{i = 1}^{N}{{Di} \cdot S_{i}}}{\sqrt{\sum\limits_{i = 1}^{N}{D_{i}^{2} \cdot {\sum\limits_{i = 1}^{N}S_{i}^{2}}}}}} & (1)\end{matrix}$

Where R_(A)(S,D) is the relevance value of the category, Di and Si arethe weighting categories assigned to the node i of the trees TD and TS,respectively (the nodes are simply processed pair-wise), and N is thetotal number of nodes.

FIG. 31 illustrates the preferred process for determining the relevancevalue of a category having a scalar structure. Once again, binary nodeweights are assigned to tree TS based upon whether a node is selected.In the Tree TD, a weight of 1.0 is assigned to the selected sub-node.Progressively lower weights are than assigned to the remainingsub-nodes, depending upon their distance from the selected sub-node. Itis presently preferred that the weight of a sub-node be multiplied by0.9 for each position that it is removed from the selected sub-node. Byassigning weights in this manner, it is possible to attribute value to asub-node in the database based upon how close it is to the selectedvalue. Thus, a record in which the selected node does not correspond tothe value in the record will still be given effect in the relevancedetermination, depending upon how close the value in that record is tothat selected value. It has been found that the cosine algorithm isunreliable when used with scalar categories, because it eliminates thecontribution of any unselected node to the relevance value. Accordingly,it is more desirable to use a relevance algorithm which does not dothis. For example, the algorithm represented by equation 2 is presentlypreferred for scalar categories.

$\begin{matrix}{{R_{B}\left( {S,D} \right)} = {1 - \frac{{\sum\limits_{i = 1}^{N}D_{i}} - S_{i}}{N}}} & (2)\end{matrix}$

Once a relevance value has been obtained for each category, these valuescan than be combined, for example by averaging, in order to arrive at arelevance value for the entire record. If such averaging is utilized, itis preferred to ignore all unselected categories in the evaluationprocess.

The process for generating a relevance value for a record is summarizedin the flow chart of FIG. 32. The process starts at block 100 and, atblock 102, the first category in the record is selected. At block 104,the relevance algorithm utilized is determined, based upon the datastructure of the category. In block 106, the weights of the respectivenodes of the selection tree TS and the data structure tree TD arecorrelated using the selected relevance algorithm. Preferably, thealgorithms discussed above are utilized.

At block 108 a test is made to determine whether all categories in therecord have been processed and, if not, the next unprocessed category isselected at block 110 and control returns to block 104 to process thenext category. If it is determined at block 108 that all categories havebeen processed, control transfers to block 112, where the relevancevalues of the categories are combined to produce the relevance value ofthe record. Preferably, this is done by averaging, as described above.At this point the process terminates, since the relevance value of therecord has been determined.

Having a relevance value for each record, it is now possible to producea report for the searcher, preferably in the order of relevance value.

Further aspects of the present invention will be described in thecontext of an alternate embodiment, which realizes an improved messageboard or user forum and also exemplifies the user reputation aspect ofthe invention.

In late 1998, a law firm “Firm 1” was losing associates faster than itcould hire them. To stem the tide, “Firm 1” decided to give allassociates a year-end “boom-year bonus” of $15,000.

At other firms, confusion reigned. Law firms had long made a point ofpaying associates the same amount from firm to firm. Should all firmsnow raise salaries to match “Firm 1”? Or could they get away withleaving things as they stood?

Firms responded inconsistently: some matched the “Firm 1” bonus, a fewincreased it, and others paid nothing. Associates who hadn't receivedbonuses were resentful, but there was little they could do.

The following year, an anonymous associate started a message board onYahoo! called “Greedy Associates.” Associates using this board hopedthat by talking about their firms online, they could put pressure on lawfirm partners to match “Firm 1” if boom-year bonuses were given a secondtime.

The logic was that an online message board would create accountability.Firms that hadn't matched “Firm 1” in 1998 thought they could get awaywith it because nobody would know. Law students considering working atthose firms would have no way of learning whether, or how much, thosefirms had paid. By creating an online message board to talk aboutsalaries and bonuses publicly, lawyers could create a repository forthis kind of information and force their firms to match market leaders.Firms that chose not to would be taken to task, and would have a hardertime recruiting new attorneys.

The Greedy Associates board was wildly popular, receiving up to 80,000hits per day. As soon as a firm decided to give (or not to give) abonus, news went out immediately. Associates sometimes learned that theyhad received bonuses on Greedy Associates before receiving an officialmemo from their firms. Greedy Associates became the new grapevine, andbefore long associates at most firms were checking the board severaltimes a day.

The board made the front page of the New York Times when gossip onGreedy Associates led New York law firms to pay large bonuses in orderto match California firms. In the past, the California raises might havebeen ignored. But with Greedy Associates publicizing the buzz amonglawyers, law firms felt they were under a microscope. They could nolonger ignore what people were saying about them online without puttingtheir reputation at risk.

For the first time lawyers had been given a conduit to exchangeinformation, and the information they exchanged was not limited tosalaries: firm culture, clients, layoffs, and general gossip were alldiscussed. Before the Internet, this would have been impossible. Now itwas easy.

Greedy Associates was popular in spite the incredibly poor quality ofits underlying technology. “This board sucks,” was the message mostcommonly posted to Greedy Associates. And it did. The fact that GreedyAssociates became so popular is a testament to the incredible demand forthe service, not the quality of the site.

Three problems stood out:

-   -   Spam. Most messages weren't worth reading. They ranged from long        rants to advertisements to messages like “Right on!” Users        looking for specific information or good conversation were        forced to wade through huge amounts of spam before finding what        they wanted.    -   Static Boards. Although there was only one Greedy Associates        board, all kinds of different people, with different interests,        were reading it. California litigators were thrown in with New        York corporate lawyers; ambulance chasers from Alaska were        grouped with tax lawyers from Texas. As a result, most users        were forced to read messages about subjects they weren't        interested in. This was just as bad as making them read spam. If        a message doesn't apply to you and you're not interested in it,        it may as well be spam.

Because of the divergent interests of its users, the original GreedyAssociates board eventually fractured into almost fifty separate boardswith names like Greedy NY Associates, Greedy SF Associates and Greedy NYTax Associates. Every variation on the theme was played. And of course,because they were far smaller than the original Greedy Associates board,each subsidiary board was far less useful.

-   -   No Real Anonymity. One of the chief reasons for the popularity        of Greedy Associates was the anonymity it offered. By speaking        under a pseudonym, people felt they could reveal more than if        their identity were known.

But as many people realized, the anonymity offered by Greedy Associateswas limited. As most sites do, Greedy Associates secretly recordedinformation about its users and would disclose this information ifserved with a court order or subpoena. As a result, people who mightotherwise have contributed to the conversation remained silent for fearof revealing their identity.

The present inventor originally set out to solve the problems observedon Greedy Associates. Efforts were focused on four discrete issues:

-   -   Dynamic. Static boards are clearly problematic, yet no message        board product provides a non-static solution. A dynamic product,        in which the contours of a “board” can expand or contract as        users desire, is required.    -   Self-Regulating. Spam and low-quality messages choke off        meaningful conversation before it ever has a chance to start. A        self-regulating board in which messages that users don't want to        see vanish before others are forced to read them results in less        spam and more high-quality dialogue.    -   Anonymous. Valuable information about the intimate details of        specific firms attracted people to Greedy Associates, but the        lack of true anonymity prevented the most interesting        information from ever being posted. The option of posting        information with true anonymity is necessary to give users the        freedom to post the kind of information that others want to see.    -   Organic. Certain areas of message boards are heavily used and        deserve to be expanded. Others are rarely used and fall into        neglect. A good product should be organic: it should respond        naturally to the demands that users place on it. Areas that are        heavily used should automatically expand; areas that are rarely        used should automatically contract (or even vanish).

Solutions Have Wide Application. It soon became apparent that theproblems observed on Greedy Associates are endemic to message boardsgenerally, and that the solutions have widespread application tovirtually any kind of online community.

As a result, instead of designing a better version of Greedy Associates,the present invention created a process and system to allow Web sites ofany kind to implement the solutions discovered.

A. Dynamic Model.

i. The Problems with Static Models.

Online speech is stored using static methods. A post might be found on aspecific “board,” an article in a “section” of a magazine, or aphotograph as part of an “album.” These storage models separate contentinto individual spaces with fixed boundaries. People know that messagesabout Honda Accords, for example, are found on the Accord bulletin boardin the Honda section, or that messages about Cisco Systems are found onthe Cisco bulletin board in the Companies section. The path to aspecific item is always the same, and follows a simple categorizationscheme.

This is a bad system. To understand why it is bad, it is useful tounderstand how a static system is structured. Consider Vault.com, apremier message board for job seekers. A simplified structural model ofVault.com's message boards relating to “Law” appears in FIG. 1.

In the system of FIG. 1, boards are grouped into three categories:Finns, Industries and Topics. This appears logical and would seem toprovide a clear framework for posting messages. But it doesn't.

a. Bonuses at “Firm 1”: A Simple Example.

Suppose a user wants to post information about bonuses at “Firm 1”.Where should he post the message so that others will find it? There arethree possibilities: The ““Firm 1”” board, the “Law” board or the“Salary Information” board.

Few users would take the time to post their message to all threerelevant boards, and if they did it would simply create another problem.People who read all three boards would find themselves reading the samemessage over and over again. Thus, there is no one logical place for auser of the above system to post a message about bonuses at “Firm 1”,and no obvious solution to this problem.

The lack of a clear answer to the question of where a message on aspecific subject should go creates difficulties for users. In the aboveexample, users may read the “Firm 1” board without ever realizing thatmessages about “Firm 1” are also posted on both the “Law” board and the“Salary Information” board. For these users, the system isunder-inclusive because it fails to show them all the messages that theywant to see. But users who look for messages about “Firm 1” bonuses onthe “Firm 1” board have the opposite problem. These users may be forcedto read through numerous messages about “Firm 1” that don't deal withbonuses. For these users, the system is over-inclusive because it showsthem many messages that they don't want to see.

b. Comparisons within Groups: A Complex Example.

Problems with static systems are even greater for users who want to postmessages about several different subjects within the same group.Suppose, for instance, that a user wants to compare the bonus given at“Firm 1” with the bonuses given at another specific firm (Firm 2”).Where should he post this message?

There are five boards where this message could reasonably be posted, butnone of them are precisely right. It could be posted to the “Firm 1”board, the ““Firm 2”” board, the “Firm 3” board, the “Law” board or the“Salary Information” board. Whichever board the information is postedto, however, it's virtually certain that many users who would find itinteresting will never see it. In some embodiments, it would not beposted to the “Firm 3” board (or other boards resulting from the filterselection of other firms that are neither “Firm 1” nor “Firm 2”). Inother embodiments, it would be posted to one or more other boardsresulting from the filter selection of other firms that are neither“Firm 1” nor “Firm 2”).

Even if the poster feels sure that he should post his message to one ofthe boards grouped under “Firms,” there's no clear answer as to which isbest. Since no answer is clearly correct, any selection is sure toconfuse users to some extent. The only board which would be clearlycorrect would be one dedicated specifically to comparisons of “Firm 1”,“Firm 2” and “Firm 3”. And no such board exists. In some embodiments, itwould not be posted to the “Firm 3” board (or other boards resultingfrom the filter selection of other firms that are neither “Firm 1” nor“Firm 2”). In other embodiments, it would be posted to one or more otherboards resulting from the filter selection of other firms that areneither “Firm 1” nor “Firm 2”).

ii. The Advantages of Dynamic Boards.

The present invention allows companies to create dynamic message boards.FIG. 2 shows one embodiment of a system utilizing the present invention.Other embodiments can remove, add to, change, and/or rearrange the showncomponents. In a dynamic system, messages are not situated in individualareas with clear boundaries. No clearly defined “boards” exist. Instead,the user selects filters which the system uses to generate “boards” froma message database. Consider how the two problems discussed in theprevious section would be solved by a dynamic system.

a. Bonuses at “Firm 1”: Solving the Simple Example.

If a company like Vault.com were using the present invention, it mightuse filter categories such as “Firms,” “Industries,” and “Topics.” Insome embodiments, the filter categories are “hardwired” into the system.In other embodiments, the filters are dynamically generated. A userinterested in bonuses at “Firm 1” would select the following filters:

Firms=“Firm 1” Topics=Salary Information

Although the user has not selected a filter for Industries, this filterwill automatically be set to “Law” because “Firm 1” is a law firm. Ifthe user had selected a banking firm, the Industries filter wouldautomatically have been set to “Banking.” The database understands therelationships between filters and fills in unselected filter boxes withappropriate information. This understanding can be either “hardwired”into the system, or can be dynamically generated. Some examples ofrelationships generally are shown in FIG. 3. Thus, even though the userhas left Industries blank:

Industries=Law 25

Now that the filters have been set, the user clicks “Apply.” Thesoftware sorts through the database and pulls out all messages, articlesand other content related to both “Firm 1” and Salary Information (areaA in FIG. 4). This information will be displayed first, in a formatindistinguishable from an ordinary message board. The Present inventionnext pulls out all information related to Law Firms (other than “Firm1”) and Salary Information (Area B). This information will be displayednext.

b. Comparisons Within Groups: Solving the Complex Example.

The advantages to this system become clearer if we reconsider thecomplex example, in which the user wanted to post a message comparingbonuses at “Firm 1”, “Firm 2” and“Firm 3”. In a dynamic system, the userwould select the following filters:

Firms=“Firm 1”    “Firm 2”   “Firm 3” Topics=Salary Information

As in the previous example, the Industries filter will automatically beset to “Law” because the firms selected are all law firms. Thus:

Industries=Law

The Present invention will sort through the database and pull out allmessages, articles and other content related to “Firm 1”, “Firm 2”,“Firm 3” or Salary Information. Some embodiments pull out contentrelated to law firm information for law firms that are none of “Firm 1”,“Firm 2”, and “Firm 3”. Some embodiments pull out content related to thelaw industry. It will then order the data so that the most relevantinformation will be displayed first. FIG. 5 shows an example of selectedcategories of content and user selected categories being used as inputsto generate relevances.

The first messages to be displayed will be those tagged with “Firm 1”,“Firm 2”, “Firm 3” and Salary Information (labeled “A” in FIG. 6). Thesemessages will be most likely to contain the content that the user islooking for. By selecting these filters the user has, in effect, createda custom “board” designed specifically for him on precisely the subjecthe is most interested in.

In one embodiment, a message relating to firm 1, firm 2, and salary israted higher than a message relating to firm 1, firm 2, and firm 3. Inanother embodiment, a message relating to firm 1, firm 2, and salary israted lower than a message relating to firm 1, firm 2, and firm 3.

The next messages to be displayed will be those labeled “B.” The Presentinvention will combine messages about “Firm 1” & “Firm 2”, “Firm 1”&“Firm 3” and “Firm 2” &“Firm 3” (all of which are also about SalaryInformation) and will sort them using a number of factors. In someembodiments, these factors can include a fuzzy math algorithm. In someembodiments, these factors can include an algorithm combining scalarvalues. After these messages have been displayed, the Present inventionwill display messages labeled “C,” which deal solely with “Firm 1”,“Firm 2” or “Firm 3” and the messages labeled “D,” which deal withSalary Information and Law Firms, but not with “Firm 1”, “Firm 2”or“Firm 3” specifically. In some embodiments, the above order can bechanged; for example, including messages which do not deal with salaryinformation.

Allowing users to display messages in this way solves the problemdescribed in the last section. Users who wish to pull up information on“Firm 1”, “Firm 2”, “Firm 3” and Salary Information will see, first andforemost, the information most interesting to them. If, while looking atthis “board,” they choose to post a message, their message willautomatically be tagged with “Firm 1”, “Firm 2”, “Firm 3” and “SalaryInformation.” It will be among the messages likely to be displayed whenanother user performs a search using the same filters.

Unlike a search that uses only Boolean keyword searching, someembodiments of the invention allow searches to yield results which maynot be 100% on point but still have relevance. For example, in anembodiment managing products, a customer can find products with varyingdegrees of relevance to the filters, and not just the 100% relevantproducts. If the merchant does not have one or more of the productssought by the customer, at least the merchant can present relatedproducts of interest to the customer.

In embodiments such as the discussed embodiment, a user can findinformation which may not be 100% on point but still have relevance.

In order to match data in a database with a given query, we takeadvantage of relationships (also known as “links”) that we establishbetween the data and the query. These relationships are often, but notalways, segmented across several different categories (such as age,height, weight, location, price, etc.).

Every piece of content in a TRANSPARENSEE™ system is tagged with a setof weighted categories. Any query made to the system is also translatedinto a set of weighted categories. Our system assigns a numerical valueto the degree of similarity (or difference) between these two sets ofweighted categories through the use of our “Similarity Algorithm”.

The steps of the Similarity Algorithm are as follows:

1) Determine the weights of an element of content's tagged categories.

2) Determine the weights of the categories used in the selection (orquery).

3) For each piece of tagged content:

-   -   3a) For each category (such as age, height, weight, location,        price, etc.).    -   3aa) Find the similarity of the content's category weights to        selection's category weights.    -   3b) Aggregate the similarities across all root categories for        this piece of content.

The output of this calculation is a mapping of content object torelevance value.

The Similarity Algorithm can be customized in several ways:

Step 2) When a selection is passed into the algorithm, the weight oneach category is either 1 or 0: 1 if the category has been explicitlyselected and 0 if it has not. The Similarity Algorithm uses therelationships (links) between categories to assign weights to categoriesthat are related to the explicitly selected categories. Theserelationships (links) could be sibling relationships, parent/childrelationships, cross-linked relationships (links to categories underother root categories) or any other type of relationship. Weightsassigned to categories as links are traversed based on the weight of theoriginating category in the link. The modifier used to assign weights tolinked-to categories is adjustable.

Step 3a) If desired, certain root categories can be ignored.

Step 3aa) The method of comparison between the category weights in theselection and the category weights in the content is customizable. Onemethod of comparison that can be used is a Cosine Coefficient algorithm.

Another method of comparison that can be used is the “SmithgateAlgorithm”, which we developed ourselves. Any other algorithm can beused to determine the degree of similarity between two pieces of taggedcontent.

Step 3b) The aggregation algorithm can take into account weights orrankings of the root categories, since certain root categories may bemore important than other root categories.

B. Rating Messages

The dynamic model described in Section A provides a powerful tool fororganizing content. Used in conjunction with a sophisticated ratingsystem, it is capable of far more.

A dynamic system automatically captures “metadata” each time a userposts a message. Examples of metadata are the filters set when a messageis posted and ratings information. Because we know which filters are setwhen a message is posted, we know (in broad terms) what the message isabout. As users rate messages, the system therefore develops asophisticated profile on which subjects users are experts on.

This profile allows the system to do two things that can't be done onstatic systems: users can screen content so that people with poorreputations on this subject are ignored; and ratings given to specificmessages can be weighted by the user's knowledge of the subject.

From a user's perspective things are simple: just point and click togive a message a rating between one and seven. Other rating systems useother scales. Some embodiments can have discrete and/or continuousrating systems. But the Present invention manages to do subtle andcomplex things with this simple rating.

i. Reputation System

Each user builds a reputation over time. This reputation is not a singlenumber, but a profile made up of many numbers. Users build reputationratings for each filter value of every message they've ever posted orrated on the system. FIG. 7 shows an example flow chart for updating auser's rating. Steps can be added, removed, changed, and/or rearranged.

There are two ways of building a reputation: posting messages and ratingmessages. Posting a message gives the system substantial data toevaluate. Reputations gained through posting are therefore difficult toinfluence once established. In contrast, rating a message gives thesystem limited data to evaluate. Reputations gained by rating aretherefore easier to influence. Thus, posting allows users to build“strong” reputations which can't easily be changed while rating messagesallows users to build “weak” reputations which can be changed quiteeasily.

a. Building a Reputation by Posting: Strong Form.

Consider an example in which a poster posts a message comparing “Firm1”, “Firm 2” and“Firm 3”. For the moment, let's contemplate only the“Firms” filter, which is set as follows:

Firms=Firm 1    Firm 2   Firm 3

In this case our rater, thinking the poster's message brilliant, givesit a 7. Our rater has already built a reputation, and his reputation forthe selected firms is:

“Firm 1” = 7 (high) “Firm 2” = 4 (medium) “Firm 3” = 1 (low)

The situation now looks like this:

Filter Value Rating Rater's Reputation “Firm 1” 7 7 “Firm 2” 4 “Firm 3”1

For each filter the rating of seven will be weighted by the rater'sreputation and then averaged into the poster's reputation. Let's gothrough this example to see how this would work.

The rater has a reputation of seven for “Firm 1”. He is an expert on thesubject. Since an expert on “Firm 1” gave a message involving “Firm 1” atop score, the poster's reputation on “Firm 1” will go up substantially.The rating of seven will be averaged into the poster's reputation on“Firm 1” and will be heavily weighted.

The rater has a reputation of four for “Firm 2”. This means that, whilenot entirely ignorant, he isn't an expert. Although he gave the messagea seven, we shouldn't trust his opinion on “Firm 2” as much as we didhis opinion on “Firm 1”. The rating of seven will be averaged into theposter's reputation for “Firm 2”, but will not be weighted as heavily ashis rating of “Firm 1”. The poster's reputation for “Firm 2” will rise,but not as much as his reputation for “Firm 1”.

As for “Firm 3”, the rater has a reputation of one. He knows nothingabout “Firm 3”, so we shouldn't trust his opinion at all. Even thoughthe rater gave this message a seven, the rating will have no weight andwill not affect the poster's reputation. In other embodiments, theweight has nonzero but low weight.

b. Building a Reputation by Rating: Weak Form.

Not all users are comfortable posting messages. For this reason, a weakform of building reputation that does not depend upon posting is alsoavailable.

All that is required of users to build this type of reputation is thatthey rate messages. Each time a user rates a message, the systemperforms a “cluster analysis” on the rating. In alternative embodiments,the reputation of the user is adjusted less frequently than every timethe user posts a message.

This involves comparing the user's rating with ratings given thatmessage by people with high reputations. If, over time, a user's ratingson a particular subject tend to correlate with the ratings of highreputation people on the same subject, we can assume that the user istrying to rate messages honestly and fairly and that he knows somethingabout the subject. His reputation in this area will rise. But if theuser's ratings tend to disagree with the ratings of people with highreputations, his reputation will fall.

A reputation built in this way is “weak” in the sense that it mayrapidly be changed by the strong form of reputation-building. Forexample, a user may build up a reputation for ““Firm 1”” over time usingthe weak method. Eventually this user may decide to post a message about“Firm 1”. If the message receives a good rating from high-reputationusers, the user's reputation for knowing about “Firm 1” will bereinforced. But if the message receives a bad rating, the user'sreputation for knowing about “Firm 1” will quickly be eroded. One or twobad “strong” ratings of posted messages are enough to destroy a “weak”reputation built up over a period of months. In other embodiments, morethan two such messages are enough to destroy the reputation.

ii. Message Ratings.

Just as users have reputations, messages have ratings. Message ratingsare determined by the scores users give them, weighted by the relevantreputation of the raters.

Let us go back to our example of the previous section. The situation wasas follows:

Filter Value Rating Rater's Reputation “Firm 1” 7 7 “Firm 2” 4 “Firm 3”1

The rater has given this message a seven. But the rater does not have aperfect reputation for all the relevant filters. He knows quite a bitabout “Firm 1”, but only a little about “Firm 2” and nothing at allabout “Firm 3”.

The system aggregates the rater's reputation in these fields using amathematical formula. In this case, the rater's aggregate reputation for“Firm 1”, “Firm 2” and “Firm 3” is four. The system will average therating of seven into the message's rating, giving it a weighting offour. FIG. 8 shows an example of calculating an aggregate reputation. Inother embodiments, nonuniform weights are given to the multiple rater'sreputations. In one embodiment, the scale of 1-7 is resealed to 0-1.Other embodiments rescale ratings to different continuous or discreteranges.

If the user had had a perfect reputation for knowing about “Firm 1”,“Firm 2” and “Firm 3”, the weighting would have been a seven. In thatcase the user's rating of seven would have been averaged into themessage rating with a weighting of seven. The message rating would counttwice as much as it did in the prior example. In some embodiments, theweight of a message has a linear relationship with the rating of themessage. In other embodiments, the weight of a message has a nonlinearrelationship with the rating of the message.

In some embodiments, a message has one rating. In other embodiments, amessage has multiple ratings, for example different ratings fordifferent filters or sets of filters.

C. Threshold Filtering.

The rating system works hand in hand with a system to filter ratedmessages. The filtering system allows users to select a rating thresholdand view only those messages with ratings above that threshold. Othermessages are not seen.

i. Method of Threshold Filtering.

To set a threshold, users click the “threshold” button. A paletteappears, containing a scatterplot as in FIG. 9. Other embodiments use aninterface other than a scatterplot, such as one or more selectors ofreputation and/or message rating. Each dot represents a message. Inother embodiments, dots represent approximations of messages and do nothave a one-to-one correspondence. By selecting a point on thescatterplot, users can choose any combination of message quality andreputation quality. In some embodiments where messages have multipleratings, such as for different filters, a user can select ratingsdirectly or indirectly. Other embodiments permit selection of justreputation or just message rating. Suppose, for example, that a userselects the point on the scatterplot as in FIG. 10.

By selecting this point the user has chosen to view messages of highmessage quality without much regard to the reputation of the poster.

A different user might have selected the point on the scatterplot as inFIG. 11.

This user has chosen to view messages posted by users with highreputations without much regard to message quality. Many users will, ofcourse, select a point like in FIG. 12:

This user wants to see only those messages of high-quality which werewritten by people with high reputations. By selecting this threshold,this user will likely see only the very best messages that have beenposted.

ii. Results of Threshold Filtering.

In combination with the reputation system, this method of thresholdfiltering allows people to build communities of self-validating experts.These experts are encouraged to post good content and to rate contentthey see accurately.

By posting good content or rating content accurately, users build highreputations. People with high reputations become community leadersbecause their voices are heard by others. People without highreputations are excluded from the community because their voices cannotbe heard.

In the diagram of FIG. 13, “Average Threshold” represents the averagecombination of reputation and message rating selected by users of acertain filter-set (such as ‘Firm 1′° ’ and “Salary Information”).

Other embodiments use an interface other than a scatterplot, such as oneor more selectors of reputation and/or message rating.

Users whose quality of speech places them above the average thresholdwill be heard. In this way, the Present invention formalizes a processthat takes place informally all the time: people who speak intelligentlyand often become recognized as authorities.

But the system does something more. Users whose quality of speech placesthem below the average threshold will, on average, not be heard. Theirspeech is never seen by the average user.

People who say foolish things or post spam will find it difficult topost messages which fall above the Average Threshold. They will quicklyestablish a poor reputation. Thus, in addition to providing incentivesto post good content, the system provides disincentives for posting badinformation. People are encouraged to say good things and discouragedfrom speaking if they have nothing good to say.

D. Implicit Reputation.

Filters often have clear relationships between them. ““Firm 1”,” forinstance, is a law firm. Thus, as described in Section III (A)(ii), when““Firm 1”” is selected (for “Firms”) “Law” is automatically selected(for “Industries”).

This means that as people build reputations in specific categories, theyautomatically build reputations in other related categories. Therelationships between related categories can be “hardwired” and/ordynamically determined. A person who builds a reputation for “Firm 1”simultaneously builds a reputation for Law. See FIG. 14.

If, after speaking well about Salaries at “Firm 1” a person decides tospeak about Salaries at Law Firms generally, they will already haveestablished a reputation for both “Law” and “Salaries.” Their advice onLaw Firms will be trusted because, by demonstrating that they know about“Firm 1”, they've shown that they know about Law Firms generally.

If they say bad things about Law Firms, their reputation for Law Firmswill decline but their reputation for “Firm 1” will be unaffected. Inother embodiments, their reputation is affected poorly. In otherembodiments, good messages raise their reputation for “Firm 1”. Afterall, they've already established that they know about “Firm 1”. The factthat they don't know about other firms doesn't diminish that.

E. Annotation System

The use of filters as described permits a unique annotation system. Thissystem lets users annotate content with their comments, which areappropriately tagged and filed by the Present invention. In this wayproprietary content becomes the seed from which thousands of relatedmessages sprout, filling the database with interesting, pre-sortedmessages. FIG. 15 shows an example flow chart of annotation posting.Steps can be added, removed, changed, and/or rearranged.

i. Creating Annotations.

Proprietary content is first tagged, sentence by sentence, withappropriate filters by the site operator. In other embodiments, taggingoccurs more frequently, for example word by word, or group of words. Inother embodiments, tagging occurs less frequently, such as inmulti-sentence blocks or paragraphs.

As shown in the paragraph of FIG. 16, the user cannot see the filtervalues attached to each sentence. These are invisible. All he can seeare the sentences about “Firm 1”. In other embodiments, the user can seeone or more filters.

The filter values come into play when the user decides to annotate asentence. Suppose that the user decides to comment on the third sentencein the above paragraph. They select the sentence to annotate, then entertheir comments, as in FIG. 17.

Since we know that the sentence being annotated is about John Doe, apartner at “Firm 1”, we can feel reasonably sure that the annotation isabout the same subject. The system therefore automatically tags theannotation with the same filters as the original sentence and files theannotation in the database using those filters. In other embodiments,filters can be added, changed, and/or subtracted, automatically or byselection.

ii. Viewing Annotations.

There are two ways to view annotations: annotation format and messageformat.

a. Annotation Format.

When viewing annotated text, users can select a sentence to view itsannotations. Thus, a user reading a description of “Firm 1” would simplyselect any sentence for more detail.

Like messages, annotations are rated and filtered. Annotations that fallabove a user's threshold are displayed. Annotations below the thresholdare not seen.

Thus by selecting any sentence in a description, a user can immediatelyread the best comments on that sentence. Comments by users withreputations for knowing the subject matter are more likely to be seenthan comments by less knowledgeable users, and good messages are morelikely to be seen than bad.

Since annotations are filed in the message database, they can also bepulled up as messages.

The annotation in diagram seven, for instance, is tagged with thefollowing filters:

Firms=“Firm 1” Topics=Hours     Partners Partners=John Doe

This annotation will therefore come up as a message whenever a user setstheir filters in a way that substantially overlaps with these filters.Thus, if a user sets their filters to ““Firm 1”” and “Hours,” thismessage is likely to be displayed. It would also be displayed during asearch for ““Firm 1”” and “Partners” or “Law Firms” and “Partners.” Andit's almost certain to be displayed in a search for “John Doe.”

For both annotations and other messages, the order in which they aredisplayed can be influenced by relevance and/or rating.

F. Since annotations can also be viewed as messages, persuading users toannotate content will seed the system with initial messages and getconversations started. As long as the site starts with content userswant to respond to, discussions will be started and placed into thesystem with enough filters attached so that appropriate messages appearduring any related search. Because each message will have many filtersattached, users will perceive the boards on the system to be full eventhough only a few messages may have been posted.

Anonymity provides a powerful incentive to speak about sensitivesubjects online. Indeed, the mere perception of anonymity felt by onlinespeakers has contributed to an enormous outpouring of gossip on the Web.But as Time Magazine reports:

-   -   Although the sites give their posters—who generally use        pseudonyms—a feeling of anonymity, they're usually not anonymous        at all. Faced with a subpoena, most sites will readily divulge a        poster's name to the authorities.

Although a lack of anonymity can create a chilling effect on speech,giving users anonymity causes other problems. Anonymous speakers are notaccountable for their speech and feel free to post spam and low-qualitymessages because speech can't be traced back to them.

The Present invention's rating and filtering systems solve theseproblems by creating accountability for anonymous speech. Users whospeak poorly or spam the system will receive low ratings. Their messageswill not be seen and they will discover that their speech has becomeinvisible to others. On the other hand, users with good reputations willbe able to speak anonymously with the knowledge that their speech willbe heard, although their names remain unknown.

The Present invention protects people's identity in two ways: its fourlevels of anonymity and its use of onion routing.

i. Four Levels of Anonymity.

The Present invention provides four different levels of anonymity. Userscan change their anonymity level before posting messages in order toensure that sensitive messages receive as much protection as theydeserve. FIG. 18 shows an example flow chart of posting at differentlevels of anonymity. Steps can be added, changed, removed, and/orrearranged. FIG. 19 summarizes key features of different levels ofanonymity. Levels can be added, removed, or changed.

a. Level One: Use of Pseudonyms.

First level anonymity allows users to post messages using a pseudonym.Unlike other message boards, the software does not ask for informationabout the user that could link the message to their true identity. Noe-mail address, credit card information or other information that couldconnect a user to the site is recorded. Information about a user'sInternet service provider or IP address is not logged. All that thesystem requests from a user—and all it knows about a user—is theirusername and password.

This means that if a site using the Present invention is subpoenaed toturn over the identity of someone who posted a particular message, itcan't. Even if site operators cooperate to the best of their ability,the limited information they have will be useless. Asked who posted aparticular message, the most they will be able to say is, “that messagewas posted by a person calling themselves ‘Daffodil.’ It was read byother users because Daffodil has a good reputation for knowing about thesubject.”

b. Level Two: Anonymous Linked.

Second level anonymity allows users to post messages as “Anonymous.”Although other users cannot tell who posted an anonymous message, thePresent invention keeps track and continues to link a user's reputationto the messages they post. Anonymous messages may therefore benefit froma poster's high reputation, and ratings given to anonymously postedmessages affect the poster's reputation.

Messages posted using level-two anonymity are sometimes called“anonymous linked” messages because although the identity of the posteris hidden to other users, the Present invention keeps track of linksbetween messages and their authors. The software “knows” who wrote whichmessage, although other users don't.

This makes the “private reply” possible. Suppose Daffodil decides topost a message critical of ‘Mr. Big,’ a partner at “Firm 1”. Daffodilhas posted messages about “Firm 1” before, and has a high reputation forknowing about the firm. She realizes, however, that readers will be ableto determine her identity if they read this message in the context ofother messages she's written.

For this reason Daffodil decides to post her message anonymously. Herhigh reputation for knowing about “Firm 1” is linked to the message, somany people will read it. And if they give it a high rating, herreputation for “Firm 1” will go up even further.

Suppose Mr. Big reads the message. He disagrees with Daffodil, butdoesn't want to speak out publicly. He can click a button on the messagemarked “private reply” and send a private reply to Daffodil's internalmailbox on the system. He can send this reply to Daffodil even though hedoesn't know that “Daffodil” is the person he's writing to. And ifDaffodil replies to him, she can choose to do so anonymously. If thiscorrespondence continues a private, detailed e-mail conversation cantake place between these two without ever risking Daffodil's identity.And if she eventually becomes convinced that she wronged Mr. Big in heroriginal message, she may decide to retract it.

What if Daffodil decides not to retract her message? Mr. Big may becomeupset enough to serve the site with a subpoena demanding Daffodil's trueidentity.

The most the site could give Mr. Big would be Daffodil's username. Buteven this might be enough to unmask Daffodil. By putting her messagetogether with other messages posted by Daffodil in the past, Mr. Big maybe able to determine Daffodil's true identity.

c. Level Three: Anonymous Unlinked.

For this reason, the Present invention offers a third level ofanonymity. Level three messages are also referred to as “anonymousunlinked.” Like level two messages, they are posted under the username“Anonymous.” But unlike level two, the system does not keep track oflinks between messages and their authors. When a message is posted, thesystem immediately stamps the message with a user's relevant reputationscores; it then severs the link between the user and the message and“forgets” the poster's identity. After a level three message has beenposted, even the site operator is unable to determine who the authorwas.

Because the message has been stamped with the reputation values of theposter, it can be filtered like any other. Messages posted by highreputation users will be seen and those posted by low reputation userswill not. But users feel secure posting level three messages becausethey know that although their messages can benefit from their reputationscores, their identities are completely protected—even from the siteoperators themselves.

d. Level Four: Complete Anonymity.

For each of levels one, two and three, users are required to log on witha username and password before posting messages. Although theiridentities are protected, some users may feel uncomfortable providingeven this limited information just prior to posting particularlysensitive messages. For this reason level four anonymity allows users topost messages without even logging in. Users are not required to giveany information at all. Since they have not given any information to thesystem, and since the Present invention does not record IP addresses,information about ISPs or place cookies on a user's machine, users canbe assured of complete anonymity when using level four anonymity.

A disadvantage to level four anonymity is that since the system doesn'tknow who the user is, they are unable to take advantage of theirreputation. As a result, few people are likely to see messages postedusing level four anonymity. This problem is not insurmountable, however.A user who posts a particularly interesting message using level fouranonymity can simply log in at a later date, find their message, andgive it a high rating (or, if they're to scared to risk themselves thisway, they can tell a friend about the message they “read” and give themenough information to easily locate it). One good rating will not besufficient to ensure that the message is widely read. But it will givethe message enough of a boost that a few more people will see it. If themessage is truly interesting and deserves to be read, it's rating willquickly soar and it will be injected into the mainstream ofconversation.

Employers sometimes keep track of the sites their employees have beento. As a result, people are often afraid to access particular sites fromwork.

FIG. 20 shows an example of onion routing. The present invention avoidsthis problem through the use of packet wrapping. By using another siteas a proxy server and “wrapping” our IP packets with theirs, we candisguise the source of our packets. If we have a partnership withYahoo!, for instance, we could route our signal through Yahoo!, whichwould cause employers to believe that their employees are using thatsite, not ours.

Since filters are used to organize TRANSPARENSEE™ sites, it is importantto ensure that sites have complete and current filter-sets. But it isdifficult and expensive for sites to keep their filters up to date inreal-time. This would require sites about law firms to know the name ofevery new law firm, and sites about restaurants to know the name ofevery new restaurant, as soon as they come into existence.

An easier way is to give users the ability to add new filters. If theuser of a job site doesn't see their firm listed, or the user of arestaurant site doesn't see a new bistro, they can add it to the filterset. Allowing users who know a subject best to find and repair weakspots in the system is the best and most cost-effective way to keepfilters current.

The potential disadvantage is that some users may insert incorrectfilters into the filter-set. This can be prevented with TRANSPARENSEE™'sreputation system.

Suppose a user notices that their law firm, “Firm 4” is not listed on aTRANSPARENSEE™ job site. The user would request that Firm 4 be added tothe filter set and would fill out a form containing basic informationabout the firm.

Since the user claims that Firm 4 is a New York law firm, it stands toreason that users with high reputations for “New York” and “Law Firm”will be in a position to know whether Firm 4 is real or not. The nexttime such users log into the system, they will see a poll in the cornerof their screen asking which of the following is a New York law firm:(1) Simpson, Thatcher & Barlett, (2) Dewey Cheatem & Howe, and (3)Bwahahahahaha :-).

Users with high reputations for “New York” and “law firms” might beexpected to answer this question correctly. But some may not. Amalicious minority of users may check the wrong box.

These users can be caught through cluster analysis. A simple algorithmallows us to determine what answers the majority of users gave andhighlights those users whose answers differed substantially. Theirentries can be disregarded and their reputations diminished. If theirreputations go down enough, they will no longer be asked to answer pollsof this type. In this way the filter-set can grow in response to theneeds of users.

It can also shrink. If users fail to use certain filters over a periodof time, those filters are removed from the filter-set.

We term the ability to grow and shrink in response to user demand an“organic” element. The present invention makes a system highly organic.The filter-set, and thus the board itself, responds to the demands ofhigh-reputation users. By responding to users in real-time and shapingitself to their needs, the system collects and verifies information morerapidly and accurately than even a large staff could. FIG. 21 shows anexample of determining a discussion rating based on multiple factors.Fewer, more, and/or different factors can be used. Such factors can alsobe used to rate filters and other features of the software.

In addition to messages, the Present invention supports polls, articles,transcripts, faxes, Word files, photos, audio and video clips and anyother type of data. These types of content can be posted to the system,indexed, searched for, filtered and rated, just like messages.

Posting an interesting fax, photo or Word file would result in asubstantial boost to a user's reputation. Indeed, certain types ofcontent are more likely to result in a reputation boost than others. Ifa user posts an internal memo about bonuses at “Firm 1” to the “Firm 1”and “Salary Information” board, his reputation in those areas willskyrocket. It will be clear to everyone using the board that this personworks at “Firm 1” and is doing his best to feed good information toothers. This effect creates a strong incentive for people to postinformation proving that they are “insiders.”

Polls can only be posted to the system by high-reputation users. At thediscretion of the poster, they may be seen only by other high-reputationusers.

Thus, a user with a high reputation for ““Firm 1”” could create a pollasking other “Firm 1” people questions about the firm. After all, whobetter to know the best questions to ask than someone who works there?People with high reputations for “Firm 1” might, the next time theylogin, see a poll by Daffodil asking what the worst thing about Firm 1'snew offices is: (1) Not enough closet space, (2) horrible shagcarpeting, or (3) other _(——————).

When enough people have answered this poll, Daffodil will have theoption of allowing others to see poll results.

Allowing only users with high reputations to post and answer polls givespeople a substantial incentive to try to obtain a high reputation.Giving them the discretion to send such polls only to other highreputation users provides a way for high reputation users to communicateonly among themselves, thus enhancing the prestige—and reward—of havinga high reputation.

Users who achieve a high reputation may also publish articles. Anarticle is more complex than a message, and can contain images (such asgraphs) and other complex attachments. More importantly, an article isposted in a prominent and fixed position on a page, making users morelikely to read articles than messages.

As with polls, allowing only users with high reputations to writearticles enhances people's desire to obtain a high reputation. Sincepeople raise their reputation by posting good content to the site, thisencourages the posting of interesting content.

The Present invention has a “chat” option, but with a difference. Anyuser party to a chat can choose to push the “record” button at any time.If a chat is being recorded, a red light appears in a corner of the chatwindow. Recorded chats can be posted to the system just like messages.

Chats may be restricted to only high reputation users. Other users won'teven be aware that a chat is taking place. Furthermore, when a chat isposted, it may take on the average reputation values of the users partyto the chat. This encourages users to invite only high reputation peopleto chat with them if they want their transcripts to be widely seen.

Pending consideration of copyright-related concerns, the software caneasily be modified to accept faxes. If this function is implemented,users will be able to fax documents to TRANSPARENSEE™ sites from anylocation. After the fax goes through, the user's fax machine will printa slip containing a confirmation number.

The next time the user goes to the site they can receive the fax thatthey sent by clicking the “Receive Fax” button and entering theconfirmation number. The fax will then appear on the user's screen andcan be posted to the system. It is not necessary to login to receive afax, and faxes can be posted to the system using any level of anonymity.

Again, pending consideration of copyright-related concerns, the softwarecan be modified to accept Word files, photos, and video clips. Just asposting a fax can demonstrate one's insider status and raise one'sreputation, so can posting an interesting file, photo, or clip.

One of the greatest advantages of the Present invention lies in thefilter selection mechanism. It feeds information to users as they makechoices, allowing them to extract information from the database on areasthey may know little about.

Consider a law student trying to decide which firms to interview with.The student knows nothing about law firms, but knows that he would liketo work at a firm with offices in New York, Palo Alto and London.

To obtain information, the student would set his filters as follows:

Industries=Law Locations=New York      Palo Alto     LondonIf he now selects the “Firms” filter, the system will show him a list oflaw firms with offices in New York, Palo Alto and London. The list mightlook like this:

Firms=Brobeck, Phleger    Coudert Brothers       Davis Polk      GibsonDunn      Morrison & Foerster      Shearman & Sterling      Skadden Arps     White & Case

These are all law firms with offices in New York, Palo Alto and London.On a conventional bulletin-board system the user would have had todetermine for himself which firms have offices in all three locations.This could take hours, but only after doing this research would he knowwhich boards are of interest to him. On a TRANSPARENSEE™ system, therelevant firms are pre-selected.

J. Wireless Clients Supported

The Present invention has been built to accommodate multiple front-ends.Thus, as wireless PDAs (such as Palm Pilots and Blackberries) becomemore commonly available, a front-end can be provided to makeTRANSPARENSEE™ sites accessible from such devices.

The present invention will be particularly useful for PDA users, sincethe small screen and low bandwidth of PDAs places a premium on theability to retrieve high quality information quickly. Discussion boards,7 in their current form, will be virtually inaccessible from PDAs due tothe amount of time it takes to find worthwhile information on them, evenwhen using a high bandwidth client. By eliminating low qualityinformation from such boards, the Present invention will make PDAs aviable device for the exchange of information between large numbers ofonline users.

User Interfaces for Performing Search Queries

As discussed above in relation to FIG. 22, a plurality of users'computers U access a content server C via a network I (e.g., theInternet). Server C provides the users U access to a content databaseCD. Database CD may provide various types of information in a pluralityof records, each record containing information and able to be parsedinto one or more categories of information. For example, the database CDmay provide information used by an online real estate or socialnetworking service (each record containing information regarding aparticular real estate or particular product item). Also connected tothe network I is a web server W which cooperates with a system S tomanage users' access to information in database CD.

Within system S, a query and search module 20 interfaces with users,permitting them to formulate requests for information from database CD.Module 20 creates, manages and maintains a structure database 10, whichcontains information describing the structural relationship betweenvarious pieces of information in the various records of the database CD.The structure database 10 may retain information regarding the structureof each category of a record. Database 10 also contains informationrelating to the structural relationship between various portions ofinformation in a received search query in a format comparable to thestructural relationship of information in database CD.

User inputs defining a search query may be received through a userinterface. In some embodiments, user input comprises search criteria(for various categories) specified by a user (e.g., as specified throughselected filter criteria, selected categories, selected multiple-choicemenus, selected values, selected ranges, etc.). The search criteriaspecified by a user may be used as inputs to the query and search module20 to determine relevant records in content database CD. Server W thenconnects the user to server C, with instructions to server C regardingwhat information is to be provided to the user from database CD.

In some embodiments, the search query (comprising a set of one or moresearch criteria of one or more categories) may be used to produce anddisplay (in the user interface) search results comprising zero or more“exact matches” and/or zero or more “non-exact matches” in contentdatabase CD. An “exact match” in content database CD may comprise an“exact matching” record having information that exactly matches allsearch criteria specified in the search query. For example, in a realestate search service, if the search query specifies a price range of X,a zip code of Y, and a property type of Z, an exact matching recordwould contain a price in the range of X, a zip code of Y, and a propertytype of Z. Note, however, that an exact matching record may also containcategories (such as a number of bedrooms, number of bathrooms, etc.)that have not been selected by the user (whereby the user has notspecified search criteria for the category) and still be considered anexact matching record, as long as the categories that are selected bythe user (e.g., price range, zip code, property type) have specifiedcriteria that exactly match the information in the record.

A “non-exact match” in content database CD may comprise a “non-exactmatching” record not having information that exactly matches all thesearch criteria specified in the search query. In some embodiments, anon-exact match may comprise a “non-exact matching” record not exactlymatching one or more search criteria (including not exactly matching anyof the search criteria) of the search query. For example, if the searchcriteria specifies a price range of X, a zip code of Y, and a propertytype of Z, a non-exact matching record may contain a price above orbelow the range of X, a zip code above or below Y, and/or a propertytype that is not Z. As such, non-exact matches may comprise records thatare close/approximate matches, but are not exact matches, to all thesearch criteria, but still have some relevance to the search query. Forexample, a non-exact match may comprise a real estate record having azip code of Y, a property type of Z, but have a price just above therange of X. A user interface may show non-exact matching records listedin an order (e.g., decreasing order) based on the relevance of thenon-exact match to the search query. In some embodiments, search methodsdiscussed herein may be used to determine a relevance value for eachrecord in a database, the relevance value representing therelevance/closeness of the record to the search criteria.

Search results comprising exact and non-exact matches may be producedusing methods and algorithms described above. For example, searchresults may be produced by maintaining information (in structuredatabase 10) regarding the structure of information in content databaseCD and using the structure database 10 to correlate the structure of asearch query to the structure of the information in the content databaseCD. As a further example, search results may be produced by the“Similarity Algorithm.”

A user interface may be provided for receiving user input for performinga search query on the content database CD, the search query comprising aset of one or more search criteria of one or more categories. The userinterface (such as, a graphical user interface) may be provided by theweb server W or content server C to receive user input from users (e.g.,through users' computers U). In some embodiments, the user interfaceprovides one or more user interface tools and/or user interfacefunctions relating to the performance of search queries on the contentdatabase CD. In some embodiments, a user input tool includes a “slider”tool associated with a particular category, the “slider” tool being usedfor changing the search criterion (category value) or the weight valueof the associated category. In response to receiving any changes(through the slider tool) in the search criterion or weight value of anassociated category, the user interface displays new search resultscomprising exact and/or non-exact matches based on the changed/newsearch criterion or weight value.

In some embodiments, a user interface tool includes a “drill down” toolfor an associated search criterion of a particular category, the drilldown tool being used to show (upon user selection of the drill downtool) records having the associated search criterion, and/or to select(upon user selection of the drill down tool) the associated searchcriterion. In response to receiving a selection of a search criterionthrough a drill down tool, the user interface displays new searchresults comprising exact and/or non-exact matches based on the newsearch criterion. In some embodiments, a drill down tool may also beused to display an “exact-match number” comprising the number of records(in content database CD) exactly matching the search criterionassociated with the drill down tool as well as other user specifiedsearch criteria (which, in some embodiments, is changed using a slidertool). In response to receiving any changes (through a slider tool) in asearch criterion, the drill down tool displays a new exact-match numberbased on the changed/new search criterion. The user interface mayfurther provide a multi-select drill-down function for allowingsimultaneous selection of two or more search criteria (associated withthe two or more drill down tools) specified for the same category.

In some embodiments, a user interface tool includes a mapping tool fordetermining address information contained in search results for thesearch query and displaying symbols representing the addresses on a map.The search results may comprise exact and/or non-exact matches that arerepresented on the map. In some embodiments, a user interface functionmay comprise a “search-result selection” function for selecting a searchresult to provide information to produce new search criteria for a newsearch query to the database CD. The new search results may compriseexact and/or non-exact matches based on the information of the selectedsearch result.

Some embodiments of a user interface are described below in relation toa real estate service or a product shopping service. These services aredescribed for illustrative purposes only and the user interfaceembodiments may be used for any other type of service (such as anyonline service, any network based service, or any non-network basedservice). Other examples include a social networking service, onlinedating service, restaurant or food survey service, news or articleservice, or any other type of special interest service.

User Interface for Selecting Search Criteria

FIG. 32 shows an exemplary screen shot of a user interface 3200 forselecting initial search criteria in a real estate service. The userinterface 3200 may be used to receive initial search criteria from theuser to search a real estate database (e.g., stored in content databaseCD). The real estate database may comprise a plurality of real estaterecords, each record containing information regarding a particular pieceof real estate. Potential users/buyers can access the database,providing various search criteria through user interfaces describedherein, to locate potential real estate for purchase.

As shown in the example of FIG. 32, the initial user interface 3200provides a plurality of user selectable categories 3201 in which tospecify search criteria (including selectable values 3205, selectablevalue ranges 3210, and/or selectable multiple-choice menus 3215). Forexample, the initial user interface 3200 may provide the user selectablecategories 3201 of “Zip Code,” “Price,” “Bedrooms,” etc. Note that auser need not select each category 3201 for specifying search criteria.In the example of FIG. 32, the “Years Old,” “Square Feet,” “Extras,” and“Property Type” categories are not selected (whereby the user has notspecified search criteria in these categories). Rather, the user maymake a selection in only those categories that he/she considersimportant. After specifying search criteria in the user interface 3200,the user may select/click on the search button 3220 to begin searchingthe real estate records stored in the real estate database based on thesearch criteria.

Category-Weight Slider Tool

FIGS. 33A-B show exemplary screen shots of user interfaces 3300implementing category-weight slider tools. FIG. 33A shows a userinterface 3300 showing search results based on the search criteria shownin FIG. 32. In some embodiments, the user interface 3300 comprises asearch-results section 3350 for displaying search results comprisingzero or more exact matches 3301 and/or zero or more non-exact matches3302. An exact match 3301 may comprise a real estate record containinginformation that exactly matches all specified search criteria (e.g.,has zip code 95129, has a price within the range of $700,000 to$750,000, has 4 bedrooms, and has 2 bathrooms). Note, however, that anexact matching record may also contain categories (e.g., “Years Old,”“Square Feet,” “Extras,” and “Property Type”) that are not selected orspecified in the search criteria.

A non-exact match 3302 may comprise a real estate record containinginformation that does not exactly match one or more specified searchcriteria (including not matching all specified search criteria). Forexample, a non-exact match 3302 may have a price just above thespecified range of $700,000 to $750,000, but may otherwise match theother search criteria. As a further example, a non-exact match 3302 mayhave more bedrooms than the specified 4 bedrooms, but may otherwisematch the other search criteria. As another example, a non-exact match3302 may have a different zip code than the specified 95129 zip code andhave more bathrooms than the specified 2 bathrooms, but may otherwisematch the other search criteria. As such, the non-exact matches 3302 maycomprise real estate records that do not exactly match the search query,but are close/approximate matches to the search query and still havesome relevance to the search query.

A user interface may show non-exact matches 3302 that are listed in anorder (in the search-results section 3350) based on the relevance of thenon-exact match 3302 to the search criteria. In some embodiments, a userinterface shows non-exact matches 3302 listed in decreasing order ofrelevance to the search criteria. In some embodiments, search methodsdiscussed herein may be used to determine a relevance value for eachrecord in a database, the relevance value representing therelevance/closeness of the record to the search criteria. As discussedabove, the various categories of search criteria may each have anassociated weight value indicating the importance of a particularcategory. The relevance value determined for a record may be based, inpart, on the weights associated with the various categories of searchcriteria.

In some embodiments, a user interface may provide a user selectablecategory-weight slider tool (associated with a particular category) forreceiving changes of the weight value of the associated category from auser. The weight of a category may indicate the importance of thecategory to the user. Changing the weight of category may change therelevance values determined for the records and, thus, may cause achange in the list ordering of the non-exact matches 3302 shown in theuser interface.

In some embodiments, increasing the weight/importance value of anassociated category increases the importance (in determining therelevance value for the record) of whether or not the record containsinformation that matches the search criterion specified for theassociated category. For example, increasing the weight of a categorymay increase the relevance value of a record (from its previousrelevance value) if the record contains information that matches thesearch criterion specified for the associated category (since the factthat the record matches the search criterion has increased inimportance). In contrast, increasing the weight of a category maydecrease the relevance value of a record (from its previous relevancevalue) if the record contains information that does not match the searchcriterion specified for the associated category (since the fact that therecord does not match the search criterion has increased in importance).

In some embodiments, decreasing the weight/importance of an associatedcategory decreases the importance (in determining the relevance valuefor the record) of whether or not the record contains information thatmatches the search criterion specified for the associated category. Forexample, decreasing the weight of a category may decrease the relevancevalue of a record (from its previous relevance value) if the recordcontains information that matches the search criterion specified for theassociated category (since the fact that the record matches the searchcriterion has decreased in importance). In contrast, decreasing theweight of a category may increase the relevance value of a record (fromits previous relevance value) if the record contains information thatdoes not match the search criterion specified for the associatedcategory (since the fact that the record does not match the searchcriterion has decreased in importance).

FIG. 33A shows an example of category-weight slider tools 3310 used toreceive changes in weight values for an associated category. Acategory-weight slider tool 3310 may receive changes in weight valuesfrom a user without the user having to manually type in new weightvalues. A user may change the weight of an associated category using thecategory-weight slider tool 3310, for example, by selecting and dragginga weight adjuster element 3312 on the category-weight slider tool 3310,or by selecting/clicking the category-weight slider tool 3310 to theleft or right of the weight adjuster element 3312 to decrease orincrease the weight value. In the example of FIG. 33A, a firstcategory-weight slider tool is used to change the weight of the “ZipCode” category and a second category-weight slider tool is used tochange the weight of the “Bedrooms” category. The search criterion/valueof the associated category specified by the user may also be shown nearthe category-weight slider tool 3310 (e.g., the search criterion/valueof “95129” is shown under the first category-weight slider tool and thecriterion/value of “4” is shown under the second category-weight slidertool). In the example of FIG. 33A, the first category-weight slider toolhas been used to decrease the weight (e.g., to a minimum weight) of the“Zip Code” category and the second category-weight slider tool has beenused to increase the weight (e.g., to a maximum weight) of the“Bedrooms” category.

As such, for a real estate record having a “4” value that matches the“4” search criterion specified for the “Bedroom” category, increasingthe weight of the “Bedroom” category may increase the relevance value ofthe real estate record from its previous relevance value. For a realestate record having a “4” value that does not match the “4” searchcriteria specified for the “Bedroom” category, increasing the weight ofthe “Bedroom” category may decrease the relevance value of the realestate record from its previous relevance value. For a real estaterecord having a “95129” value that matches the “95129” search criteriaspecified for the “Zip Code” category, decreasing the weight of the “ZipCode” category may decrease the relevance value of the real estaterecord from its previous relevance value. For a real estate recordhaving a “95129” value that does not match the “95129” search criteriaspecified for the “Zip Code” category, decreasing the weight of the “ZipCode” category may increase the relevance value of the real estaterecord (from its previous relevance value).

FIG. 33A shows examples of category-weight slider tools used to changethe weight of an associated category having a user specified value (suchas “95129” or “4”). However, in other embodiments, the category-weightslider tools may be used to change the weight of an associated categoryhaving any other type of user specified search criterion (e.g., asspecified through selected filter criteria, selected multiple-choicemenus, selected ranges, etc.). For example, the user interface mayprovide a category-weight slider tool to change the weight of the“Price” category having a selected value range, or provide acategory-weight slider tool to change the weight of the “Extras”category having selected multiple-choice menus, etc.

Changing one or more weights of one or more categories may change therelevance values determined for records of the database (since therelevance values are determined, in part, based on the weights of thecategories). As such, upon the user interface receiving (through acategory-weight slider tool) a change of a weight of a categoryspecifying a new weight, the list ordering of the non-exact matches 3302shown in the user interface may also change based the new relevancevalues determined for the non-exact matches 3302 using the new weightvalue. In some embodiments, the non-exact matching records 3302 arelisted in decreasing order of relevance so that a non-exact matchingrecord 3302 having the highest determined relevance value is displayedon top of the search-results section 3350 and a non-exact matchingrecord 3302 having the lowest determined relevant value is displayed onbottom of the search-results section 3350. In other embodiments, thenon-exact matching records 3302 are listed in a different order ofrelevance.

FIG. 33B shows a user interface 3300 showing exemplary search resultsbased on the changed/new category weights shown in FIG. 33A. Note in theexample of FIG. 33A, the first category-weight slider tool has been usedto decrease the weight (e.g., to a minimum weight) of the associated“Zip Code” category and the second category-weight slider tool has beenused to increase the weight (e.g., to a maximum weight) of the“Bedrooms” category. As such, the non-exact matching records 3302 havinga “4” Bedroom value (that matches the “4” search criterion specified forthe Bedroom category) have increased relevance values. Therefore, inresponse to the new category weights, the user interface 3300 displaysthese non-exact matching records 3302 in higher ordered positions in thelist of the non-exact matches 3302 (as shown in the search-resultssection 3350). Also, the non-exact matching records 3302 having a“95129” Zip Code value (that matches the “95129” search criterionspecified for the Zip Code category) have decreased relevance values.Therefore, in response to the new category weights, the user interface3300 displays these non-exact matching records 3302 in lower orderedpositions in the list of the non-exact matches 3302 (as shown in thesearch-results section 3350). As the example of FIG. 33B shows, a record(e.g., “A7”) having a matching Bedroom value and a non-matching Zip Codevalue will have a higher determined relevance value (and thus bedisplayed in a higher position in the user interface) than a record(e.g., “A4”) having a non-matching Bedroom value and a matching Zip Codevalue (since the weight of the Bedroom category is set higher than theweight of the Zip Code category).

In some embodiments, the user interface dynamically shows new listorderings of the non-exact matches 3302 in the search-results section3350 in real-time based on one or more new weights of one or morecategories (received through one or more category-weight slider tools3310). In these embodiments, changes in the list ordering of thenon-exact matches 3302 may also be shown dynamically and in real-time ascategory weights are changed by the user (using the category-weightslider tools 3310). The new list orderings of the non-exact matches 3302may be shown dynamically and in real-time as category weights arechanged, without requiring the user to type in new category weights orto otherwise initiate displaying the new list orderings (e.g., byselecting/clicking the search button 3220 again to begin a new search).As such, category weights can be continually revised using thecategory-weight slider tools 3310 as new list orderings of non-exactmatches 3302 are shown in the user interface. For example, as a userdecreases the weight of the Zip Code category and increases the weightof the Bedroom category in FIG. 33A, the list ordering shown in FIG. 33Bmay be dynamically and in real-time produced based on the changedcategory weight(s) and displayed by the user interface 3300.

Category-Value Slider Tool

FIGS. 34A-B show exemplary screen shots of user interfaces 3400implementing user selectable category-value slider tools. FIG. 34A showsa user interface 3400 showing search results (in a search-resultssection 3350) based on the search criteria shown in FIG. 32. The userinterface 3400 displays search results that may include zero or moreexact matches 3301 and/or zero or more non-exact matches 3302. In someembodiments, a user interface may provide a category-value slider toolthat is associated with a particular selected category. Thecategory-value slider tool may be used for receiving changes in thesearch criterion of the associated selected category from a user.Changing the search criterion may change the search results (includingexact matching records 3301 and non-exact matching records 3302), aswell as the list ordering of the non-exact matching records 3302 shownin the user interface (as the relevance values determined for therecords may change). Upon receiving a new search criterion of a categoryfrom the user (through a category-value slider tool), the user interface3400 may display one or more new exact matching records 3301 and/or anew list ordering of the non-exact matching records 3302 based on thenew search criterion.

FIG. 34A shows an example of category-value slider tools 3410 used forreceiving changes in search criteria of an associated category. A usermay change a search criterion comprising a category value (e.g., anumber of Bathrooms) using the category-value slider tool 3410, forexample, by selecting and dragging a value adjuster element 3412 on thecategory-value slider tool 3410, or by selecting/clicking thecategory-value slider tool 3410 to the left or right of the valueadjuster element 3412 to decrease or increase the value. Acategory-value slider tool 3410 may also be used to change a searchcriterion comprising a selected range of values (e.g., a price range),for example, by selecting and dragging a minimum value adjuster element3415 or a maximum value adjuster element 3420 on the category-valueslider tool 3410 to change the minimum and maximum range of values.

In the example of FIG. 34A, a first category-value slider tool is usedto change a search criterion comprising a range of values for the“Price” category and a second category-value slider tool is used tochange a search criterion comprising a value for the “Bathrooms”category. As such, FIG. 34A shows examples of category-value slidertools used to change a search criterion comprising a value or a range ofvalues. However, in other embodiments, a category-value slider tool maybe used to change any other type of specified search criterion (e.g., asspecified through selected filter criteria, selected multiple-choicemenus, etc.). Note in the example of FIG. 34A, the first category-valueslider tool has been used to change the search criterion to “800 k to850 k” in the “Price” category and the second category-value slider toolhas been used to change the search criterion to “3” in the “Bathrooms”category. As the user changes the search criterion, the new searchcriterion may be shown near the category-value slider tool 3410 (e.g.,the new range of “800 k to 850 k” is shown under the firstcategory-value slider tool and the new value of “3” shown under thesecond category-value slider tool).

FIG. 34B shows a user interface 3400 showing exemplary search resultsbased on the change of search criteria shown in FIG. 34A. In someembodiments, the user interface dynamically shows one or more new exactmatches 3301 in real-time as a user changes one or more search criteriaof one or more categories (using one or more category-value slider tools3410). In some embodiments, the user interface dynamically shows newsearch results as the user changes search criteria of only a sub-set ofcategories. The new exact matches 3301 may be shown dynamically and inreal-time as search criteria are changed, without requiring the user totype in new search criteria or to otherwise initiate displaying of newsearch results (e.g., by selecting/clicking the search button 3220 againto begin a new search). In some embodiments, new list orderings of thenon-exact matches 3302 are also displayed by the user interfacedynamically and in real-time as search criteria are changed (using thecategory-value slider tools 3410), without requiring the user to type innew search criteria or to otherwise initiate displaying of new listorderings (e.g., by selecting/clicking the search button 3220 again tobegin a new search). As such, search criteria can be continually revisedusing the category-value slider tools 3410 as new exact matches 3301 andnew orderings of non-exact matches 3302 may be dynamically and inreal-time shown in the user interface.

Mapping Tool

FIGS. 35A-B show exemplary screen shots of user interfaces 3500implementing a mapping tool. FIG. 35A shows a user interface 3500showing exemplary search results (in a search-results section 3350)based on the search criteria shown in FIG. 32. The search-results userinterface 3500 displays search results that may include zero or moreexact matches 3301 and/or zero or more non-exact matches 3302. In someembodiments, a user interface may provide a mapping tool 3510 thatdetermines address/location information contained in the exact matchingrecords 3301 and/or non-exact matching records 3302 and displays symbolsrepresenting the records (using the address/location information) on amap 3515. The map 3515 may display a first symbol 3520 (e.g., a shadedsymbol) representing exact matches 3301 and a second symbol 3525 (e.g.,a non-shaded symbol) representing non-exact matches 3302, the first andsecond symbols being different in appearance.

The mapping tool 3510 may provide one or more category-weight slidertools 3310 used to change weights of one or more categories and/or oneor more category-value slider tools 3410 used to change search criteriaof one or more categories. FIG. 35A shows an example of acategory-weight slider tool 3310 used to change the weight of a “Street”category and a category-value slider tool 3410 used to change searchcriterion (comprising a range value) of the “Street” category. In theexample of FIG. 35A, the weight of the “Street” category is initiallyset to a relatively low value and the range value of the “Street”category is initially set to “10 to 40” (indicated by the dashed linesin the map 3515). The search results shown in FIG. 35A are producedbased on these initial settings (as well as based on the initial searchcriteria shown in FIG. 32). The map 3515 displays symbols representingthe exact matches 3301 and non-exact matches 3302 of the search results.As shown in the map 3515, since the weight of the “Street” category isinitially set to a relatively low value, the search results includeseveral non-exact matches 3302 that are outside the specified range ofstreets “10 to 40” (indicated by the dashed lines in the map 3515).

FIG. 35B shows an example of where the category-weight slider tool 3310is used to change the weight of a “Street” category to a relatively highvalue and the category-value slider tool 3410 is used to change therange value of the “Street” category to “20 to 30” (indicated by thedashed lines in the map 3515). FIG. 35B also shows the new searchresults that are produced based, in part, on these new settings and themap 3515 displays symbols representing the exact matches 3301 andnon-exact matches 3302 of the new search results. As shown in the map3515, since the weight of the “Street” category is changed to arelatively high value, the search results do not include non-exactmatches 3302 that are outside the new specified range of streets “20 to30” (indicated by the dashed lines in the map 3515).

In some embodiments, the mapping tool 3510 shows symbol representationsfor a predetermined number of non-exact matches 3302 having the highestrelevance values. For example, the mapping tool 3510 may show symbolrepresentations for only the top five non-exact matches 3302 having thefive highest relevance values. As new weight values of a category arereceived (through a category-weight slider tool 3310) and/or new searchcriteria of a category are received (through a category-value slidertool 3410) from a user, the non-exact matches 3302 having the highestrelevance values may also change. As such, the mapping tool 3510 mayshow symbol representations for new non-exact matches 3302 having thehighest relevance values based on the new category weights and/or newsearch criteria.

In some embodiments, the user interface 3500 dynamically shows newsearch results (comprising exact matches 3301 and/or non-exact matches3302) as well as new symbol representations of the search results on amap 3515 in real-time as it receives new weight values of a category(through a category-weight slider tool 3310) and/or new search criteriaof a category (through a category-value slider tool 3410) from a user.As such, the user interface 3500 displays changing search results andchanging symbol representations of the search results on a map 3515dynamically and in real-time as a user continually changes one or morecategory weights and/or continually changes search criteria of one ormore categories, without requiring the user to type in new categoryweights and/or new search criteria or to otherwise initiate display ofthe new search results and new symbol representations.

Drill Down Tools

In some embodiments, a user interface may provide a user input toolcomprising a “drill down” tool for an associated search criterion of aparticular category. The drill down tool may be used to show (upon userselection of the drill down tool) records having the associated searchcriterion, and/or to select (upon user selection of the drill down tool)the associated search criterion. In response to receiving a selection ofa search criterion through a drill down tool, the user interfacedisplays new search results comprising exact and/or non-exact matchesbased on the new search criterion. In some embodiments, a drill downtool may also be used to display a “exact-match number” comprising thenumber of records (in content database CD) exactly matching the searchcriterion associated with the drill down tool as well as other userspecified search criteria (which, in some embodiments, is changed usinga category-value slider tool). In some embodiments, in response toreceiving any changes (through a category-value slider tool 3410) in asearch criterion, the drill down tool displays a new exact-match numberbased on the changed/new search criterion. As discussed below, in someembodiments, a drill down tool comprises a text component, matchingnumber component, and/or a criterion selection component.

FIGS. 36A-D show exemplary screen shots of user interfaces 3600implementing drill down tools. FIG. 36A shows an exemplary screen shotof a user interface 3600 for selecting initial search criteria in aproduct shopping service for digital cameras. In the example of FIG.36A, the user interface 3600 may be used to receive initial searchcriteria from the user to search a product database (e.g., stored incontent database CD). The product database may comprise a plurality ofproduct records of digital cameras, each record containing informationregarding a particular digital camera. Potential users/buyers can accessthe database, providing various search criteria through user interfacesdescribed herein, to locate potential digital cameras for purchase.Although some embodiments below relate to a product shopping service anddigital camera products, other embodiments may relate to any other typeof service and/or product.

As shown in the example of FIG. 36A, the user interface 3600 provides aplurality of user selectable drill down tools 3601. Each drill down toolmay be associated with a particular search criterion of a particularcategory. A drill down tool 3601 may comprise a text component 3605, amatching number component 3610, and/or a criterion selection component3615. The text component 3605 may comprise text (e.g., “100-200,” “6MP,” etc.) showing the particular search criterion of the particularcategory (e.g., “Price,” “Resolution,” etc.) associated with the drilldown tool. The matching number component 3610 may comprise text showingthe “exact-match number” comprising the number of records (in contentdatabase CD) having the associated search criterion as well as any otheruser specified search criteria (i.e., the number of records exactlymatching the associated search criterion and any other specified searchcriteria). To illustrate, in the example of FIG. 36A, the text “103”(displayed between parentheses) indicates there are 103 digital-camerarecords in the database having the search criterion “100-200” for the“Price” category. The user interface 3600 may also show informationregarding a plurality of records 3620 for a plurality of digital cameraproducts. Information displayed for a record may include a Product Name(e.g., Na, Nb, Nc, etc.) and values for particular categories (such as“Price,” “Resolution,” etc.).

The text component 3605 and the matching number component 3610 of adrill down tool 3601 may be user selectable. Upon receiving a userselection of either the text component 3605 or the matching numbercomponent 3610, the particular search criterion associated with thedrill down tool 3601 is selected and search results may be producedcomprising exact matching records having the particular searchcriterion. The user interface 3600 may show the search results (in asearch-results section 3350) by clearing from display any previouslyshown records (by no longer displaying the previously shown records) anddisplaying only search results comprising exact matching records havingthe associated search criterion.

FIG. 36B shows an exemplary screen shot of the user interface 3600 aftera user selects the text component 3605 or the matching number component3610 of the drill down tool 3601 (shown in boldface) for the associatedsearch criterion “200-300” for the “Price” category. As shown in theexample of FIG. 36B, the user interface 3600 no longer displays thepreviously shown records (as shown in FIG. 36A) and displays only searchresults comprising exact matching records having the associated searchcriterion “200-300” for the “Price” category (e.g., comprising 95records in the database). The user interface 3600 may also display drilldown tools 3601 for search criteria of only non-selected categories(e.g., categories other than “Price,” such as “Resolution,” “LCD,”etc.). The user interface 3600 may also comprise a currentsearch-criteria area 3625 displaying current search criteria specifiedby the user thus far.

In some embodiments, selection of a drill down tool 3601 is used tospecify the search criterion associated with the drill down tool 3601 toproduce and display new search results based on the associated searchcriterion. In these embodiments, upon receiving a selection of the drilldown tool, the user interface displays (in the search-results section3350) exact and/or non-exact matching records based on the associatedsearch criterion and all other search criteria received thus far. FIG.36C shows an exemplary screen shot of the user interface 3600 of FIG.36B after a user selects the text component 3605 or the matching numbercomponent 3610 of the drill down tool 3601 (shown in boldface) for theassociated search criterion “3” for the “Rating” category.

As shown in the example of FIG. 36C, the current search-criteria area3625 of the user interface displays the current search criteriaspecified thus far by the user (e.g., “Price: 200-300 Rating: 3”). Asshown in the example of FIG. 36C, the user interface 3600 displayssearch results based on the current search criteria, the search resultscomprising exact matching records 3301 and/or non-exact matching records3302. The exact matching records 3301 may comprise records matching thecurrent search criteria “200-300” for the “Price” category and “3” forthe “Rating” category (comprising 15 records in the database). Thenon-exact matching records 3302 may comprise records not matching one ormore of the current search criteria (e.g., having a “3” for the “Rating”category but not having “200-300” for the “Price” category, etc.). Theuser interface 3600 may also display drill down tools 3601 for searchcriteria of non-selected categories (e.g., categories other than “Price”and “Rating,” such as “Resolution,” “LCD,” etc.).

Criterion Selection Component of a Drill Down Tool

In some embodiments, a drill down tool 3601 further comprises acriterion selection component 3615. The criterion selection component3615 may comprise a user-selectable area (e.g., box) for selecting theparticular search criterion associated with the drill down tool. Uponselecting the criterion selection component 3615, the user interface3600 may display exact matching records having the associated searchcriterion and other specified search criteria while also continuing todisplay any previously shown exact matching records. In someembodiments, the user interface 3600 displays these exact matchingrecords as the first listings of the exact matching records (at the topof the “Exact Matches” section of the user interface 3600).

FIG. 36D shows an exemplary screen shot of the user interface 3600 ofFIG. 36C after a user selects the criterion selection component 3615 ofthe drill down tool 3601 (shown in boldface) for the associated searchcriterion “8&up” for the “Resolution” category. As shown in the exampleof FIG. 36D, the current search-criteria area 3625 of the user interfacedisplays the current search criteria specified thus far by the userthrough the drill down tools 3601 (e.g., “Price: 200-300 Rating: 3Resolution: 8”). As shown in the example of FIG. 36D, the user interface3600 may display the two exact matching records having the new searchcriterion (“8&up” in the “Resolution” category) and all other specifiedsearch criteria as the first listings of the exact matching records (atthe top of the “Exact Matches” section of the user interface 3600). Theuser interface 3600 may also continue to display any previously shownexact matching records (i.e., records exactly matching all previoussearch criteria specified prior to the new search criterion selectedusing the criterion selection component 3615). As shown in the exampleof FIG. 36D, the user interface 3600 may also display new non-exactmatches 3302 based on the new search criterion (“8&up” in the“Resolution” category) and all other specified search criteria. Thenon-exact matching records 3302 may comprise records not having one ormore of the current search criteria (e.g., having an “8&up” in the“Resolution” category, a “3” for the “Rating” category, but not having“200-300” for the “Price” category, etc.).

In some embodiments, upon selection of a criterion selection component3615 of a drill down tool 3601 for an associated search criterion of anassociated category, the user interface 3600 may continue to displaydrill down tools 3601 for search criteria of the particular category.For example, as shown in FIG. 36D, the user interface 3600 continues todisplay drill down tools 3601 for search criteria of the “Resolution”category. The user interface 3600 may also update the matching numbercomponents 3610 of the drill down tools 3601 to display text showing the“exact-match number” of records having the current search criteriaspecified thus far. As shown in the example of FIG. 36D, the matchingnumber components 3610 of the drill down tools 3601 display the numberof records having the current search criteria “200-300” for the “Price”category, “3” for the “Rating” category, and “8&up” for the “Resolution”category.

The user may also de-select the criterion selection component 3615 of adrill down tool 3601 to deselect the associated search criterion. Uponde-selection of the criterion selection component 3615, the userinterface 3600 may no longer display exact matching records having theassociated search criterion while also continuing to display anypreviously shown exact matching records. In some embodiments, the userinterface 3600 removes the de-selected records from the first listingsof the exact matching records (at the top of the “Exact Matches” sectionof the user interface 3600). FIG. 36C shows an exemplary screen shot ofthe user interface 3600 of FIG. 36D after a user de-selects thecriterion selection component 3615 of the drill down tool 3601 (shown inboldface) for the associated search criterion “8&up” for the“Resolution” category.

As shown in the example of FIG. 36C, the current search-criteria area3625 shows that the search criterion “8&up” for the “Resolution”category has been de-selected. Also, the user interface 3600 no longerdisplays the two exact matching records having the search criterion“8&up” in the “Resolution” category as the first listings of the exactmatching records (at the top of the “Exact Matches” section of the userinterface 3600). The user interface 3600 does so while continuing todisplay any previously shown exact matching records. The user interface3600 may also display non-exact matches 3302 based on previous searchcriteria (and no longer based on the de-selected search criterion “8&up”in the “Resolution” category).

Multi-Select Drill-Down Function

In some embodiments, the user interface may further provide a“multi-select drill-down” function for receiving two or moreuser-selections of two or more drill down tools 3601 (using two or morecriterion selection components 3615) on a single instance of a userinterface 3600 (e.g., on a single screenshot/page). In theseembodiments, two or more search criteria (associated with the two ormore drill down tools 3601) for a same category may be simultaneouslyselected/specified by a user (through the two or more criterionselection components 3615). FIGS. 36E-F show exemplary screen shots ofuser interfaces 3800 providing the multi-select drill-down function.

FIG. 36E shows an exemplary screen shot of the user interface 3600 ofFIG. 36A after a user selects the criterion selection component 3615 ofthe drill down tool 3601 (shown in boldface) for the associated searchcriterion “1-2 in” for the “LCD Size” category. As shown in the exampleof FIG. 36E, the current search-criteria area 3625 of the user interfacedisplays the current search criteria specified thus far by the userthrough the drill down tools 3601 (e.g., “LCD Size: 1-2 in”). Uponselection of a criterion selection component 3615 of a drill down tool3601 for an associated search criterion of an associated category, theuser interface 3600 may continue to display drill down tools 3601 forsearch criteria of the selected category. For example, as shown in FIG.36E, the user interface 3600 continues to display drill down tools 3601for search criteria of the “LCD Size” category, even though a selectionof the drill down tool 3601 for the search criterion “1-2 in” hasalready been received for the “LCD Size” category. The user interface3600 may also update the matching number components 3610 of each drilldown tool 3601 to display text showing the “exact-match number” ofrecords comprising the number of records having the search criterionassociated with the drill down tool 3601 as well as the current searchcriteria. As shown in the example of FIG. 36E, the matching numbercomponents 3610 of the drill down tools 3601 display the number ofrecords having the current search criteria “1-2 in” for the “LCD Size”category.

In some embodiments, the multi-select drill-down function allows theuser to simultaneously select one or more additional search criteria(associated with one or more additional drill down tools 3601) of thepreviously selected “LCD Size” category. In these embodiments, when twoor more search criteria of the same category are simultaneously selectedby a user (through the two or more drill down tools 3601), the matchingnumber component 3610 of a drill down tool 3601 may display an“any-match” number comprising the number of records having the searchcriterion associated with the drill down tool 3601 as well any of thetwo or more search criteria specified for the same category. The“any-match” number may be displayed rather than the “exact-match number”which, as discussed above, comprises the number of records having thesearch criterion associated with the drill down tool 3601 and each ofthe current search criteria (which in this case may result in zeromatching records).

FIG. 36F shows an exemplary screen shot of the user interface 3600 ofFIG. 36E after a user further selects the criterion selection component3615 of the drill down tool 3601 (shown in boldface) for the associatedsearch criterion “2-3 in” for the previously selected “LCD Size”category. As shown in the example of FIG. 36F, the currentsearch-criteria area 3625 of the user interface displays the currentsearch criteria specified thus far by the user through the drill downtools 3601 (e.g., “LCD Size: 1-2 in” and “LCD Size: 2-3 in”), whereintwo or more of the current search criteria are specified for the samecategory. In some embodiments, the user interface 3600 may also updatethe matching number components 3610 of each drill down tool 3601 todisplay text showing the “any-match number” of records having the searchcriterion associated with the drill down tool 3601 as well any of thetwo or more search criteria specified for the same category.

As shown in the example of FIG. 36F, the matching number components 3610of the drill down tools 3601 display the number of records having itsassociated search criterion and also having either the search criterion“1-2 in” or the search criterion “2-3 in” for the “LCD Size” category.As such, in comparison to FIG. 36E, each drill down tool 3601 nowdisplays the number of records having its associated search criterionand the search criterion “1-2 in” for the “LCD Size” category plus thenumber of records having its associated search criterion and the searchcriterion “2-3 in” for the “LCD Size” category. In other words, firstand second search criteria for the same category may be simultaneouslyselected using the drill down tools, where the any-match numbercomprises the number of records comprising information that matches theassociated search criterion and the first search criterion selected fora first category plus the number of records comprising information thatmatches the associated search criterion and the second search criterionselected for the first category. Thus, as further search criteria forthe same category are selected (through drill down tools 3601), eachdrill down tool 3601 is continually updated to display the total sum ofrecords having its associated search criterion and any of the searchcriteria selected for the same category.

Category-Value Slider Tools Used with Drill Down Tools

In some embodiments, a user interface may provide one or morecategory-value slider tools 3410 for use in conjunction with one or moredrill down tools 3601. As discussed above, a category-value slider tool3410 may be associated with a particular category and is used by a userto change search criterion of the associated category. As discussedabove, a drill down tool 3601 may be associated with a particular searchcriterion of a particular category and may comprise a matching numbercomponent 3610 showing an “exact-match number” comprising the number ofrecords (in a database) having information that exactly matches theassociated search criterion and any other specified search criteria.

In these embodiments, upon a category-value slider tool 3410 receiving anew search criterion for the associated category from the user, eachmatching number component 3610 of each drill down tool 3601 may beupdated to show (dynamically and in real-time) the “exact-match” numberof records exactly matching the search criterion of the categoryassociated with the drill down tool 3601 and the new search criterion ofthe category associated with the category-value slider tool 3410 (aswell as any other user specified search criteria). As such, as the userinputs new search criterion of a category using a category-value slidertool 3410, the matching number components 3610 of the drill down tools3601 may display new exact-match numbers based on the new searchcriterion received through the category-value slider tool 3410. Thematching number components 3610 may be updated dynamically and inreal-time as search criteria are changed (via the category-value slidertool 3410), without requiring the user to type in new search criteria orto otherwise initiate the display of the new exact-match numbers.

FIGS. 37A-B show exemplary screen shots of user interfaces 3700implementing category-value slider tools for use in conjunction withdrill down tools. FIG. 37A shows the user interface 3700 of FIG. 36C butfurther providing a category-value slider tool 3410. In the example ofFIG. 37A, a category-value slider tool 3410 is provided to change asearch criterion comprising a range of values for the “Price” category.In FIG. 37A, the category-value slider tool 3410 has been used to changethe previous search criterion of “200 to 300” in the “Price” category tothe new search criterion of “300 to 400” in the “Price” category. As theuser changes the search criterion, the new search criterion may be shownnear the category-value slider tool 3410.

FIG. 37B shows an exemplary user interface 3700 based on the change ofsearch criterion shown in FIG. 37A. As shown in FIG. 37B, the currentsearch-criteria area 3625 of the user interface 3700 displays thecurrent search criteria specified thus far by the user through the drilldown tools 3601 and the category-value slider tool 3410 (e.g., “Price:300-400 Rating: 3”). When the user uses the category-value slider tool3410 to specify a new search criterion for the “Price” category, eachmatching number component 3610 of each drill down tool 3601 is updatedto show (dynamically and in real-time) the number of records exactlymatching the search criterion of the category associated with the drilldown tool 3601 and the new search criterion of the category associatedwith the category-value slider tool 3410 (as well as any other userspecified search criteria).

For example, for the drill down tool 3601 with associated searchcriterion “7” in the “Resolution” category, the matching numbercomponent 3610 is updated to show (dynamically and in real-time) thateleven records exactly match the search criterion of “7” in the“Resolution” category, the category associated with the drill down tool3601, the new search criterion of “300 to 400” in the “Price” category,and the user specified search criterion of “3” in the “Rating” category.As such, the matching number components 3610 in FIG. 37B have beenupdated/changed (dynamically and in real-time) based on the new searchcriterion for the “Price” category inputted via the category-valueslider tool 3410, without requiring the user to type in the new searchcriterion or to otherwise initiate the updating of the matching numbercomponents 3610.

Note that when the user uses the one or more category-value slider tools3410 to specify one or more new search criteria for one or morecategories (e.g., for the “Price” category), the user interface 3700also dynamically and in real-time shows new search results based on theone or more new search criteria, the search results comprising exactmatching records 3751 and/or non-exact matching records 3752. In someembodiments, the user interface 3700 may further provide one or morecategory-weight slider tools 3310. As discussed above, a category-weightslider tool 3310 may be associated with a particular category and isused by a user to change the weight of the associated category. As theuser changes the weight of one or more categories using the one or morecategory-weight slider tools 3310, the user interface 3700 alsodynamically and in real-time shows search results based on the one ormore new category weights, the search results comprising exact matchingrecords 3751 and/or non-exact matching records 3752.

Using a Search Result to Specify Search Criteria

In some embodiments, a user interface may provide a “search-resultselection” function for selecting a particular search result as searchcriteria for a new search query to a database. In these embodiments, inany of the user interfaces discussed above, each search result/recordmay be made user selectable. Upon selection of a search result/record(comprising an exact or non-exact matching record), the user interfacemay retrieve information of the selected search result/record from thecontent database CD. As discussed above, a record may contain variouspieces of information (e.g., relating to a particular real estate,product, candidate, etc.). The information in the record may be parsedinto a plurality of categories and a plurality of values, each valuerelating to a particular category.

The user interface may then use the information of the selected searchresult/record (comprising a plurality of values for the plurality ofcategories) as new search criteria for a new search query to thedatabase. Using the new search criteria (based on the information of theselected search result/record), the user interface may produce and showsearch results comprising exact and/or non-exact matching records. Assuch, the user interface may show other records in the database CD thatexactly match the selected search result/record and/or show otherrecords in the database CD that are similar to the selected searchresult/record.

FIGS. 38A-B show exemplary screen shots of user interfaces 3800providing the search-result selection function for selecting aparticular search result as search criteria for a new search query to adatabase. FIG. 38A shows an exemplary user interface 3700 based onselecting the search result/record having address “A7” from the searchresults shown in FIG. 33A. Upon selection, the user interface 3800 hasretrieved the information for the selected “A7” search result/recordfrom the content database CD and the information has been parsed into aplurality of categories 3801 and a plurality of values 3805, each value3805 relating to a particular category 3801. The user may then selectthe search button 3820 to initiate a new search query on the database CDusing the plurality of values 3805 for the plurality of categories 3801as new search criteria for the new search query.

FIG. 38B shows an exemplary user interface 3700 showing search resultsbased on the information of the selected search result/record shown inFIG. 38A. Using the new search criteria based on the selected searchresult/record, the user interface 3800 may produce and show searchresults comprising one or more exact matching records 3301 and/or one ormore non-exact matching records 3302. As such, the user interface 3800may show other records in the database CD that exactly match theselected search result/record and/or show other records in the databaseCD that are similar to the selected search result/record. In someembodiments, the user interface may produce and show the search results(based on the information of the selected search result/record) directlyupon receiving a selection of the search result, and without firstshowing the information of the selected search result/record. Forexample, in these embodiments, the user interface 3800 may not show theinformation of the selected search result shown in FIG. 38A and produceand show the search results shown in FIG. 38B directly upon receivingthe user selection of the “A7” search result/record.

In some embodiments, the search-result selection function may be used inany of the user interfaces (providing exact and/or non-exact matches)discussed herein and in conjunction with any of the user interface toolsdescribed herein (such as the category-weight slider tool 3310,category-value slider tool 3410, mapping tool 3510, and/or drill downtool 3601). In some embodiments, any of the user interface tools orfunctions described herein may be used in any combination, and beimplemented in a user interface providing exact and/or non-exactmatches. For example, one or more category-weight slider tools, one ormore category-value slider tools, one or more mapping tools, one or moredrill down tools, the multi-select drill-down function, thesearch-result selection function, or any combination thereof, may beprovided in a same user interface, the user interface showing searchresults comprising exact and/or non-exact matches.

FIG. 39 shows an exemplary screen shot of a user interface 3900implementing various user interface tools and functions describedherein. As shown in the example of FIG. 39, the user interface 3900provides a category-weight slider tool 3310, a category-value slidertool 3410, a mapping tool 3510, drill down tools 3601, and asearch-result selection function. The user interface 3900 also showssearch results comprising exact matches 3301 and/or non-exact matches3302.

Although preferred embodiments of the invention have been disclosed forillustrative purposes, those skilled in the art will appreciate thatmany additions, modifications and substitutions are possible withoutdeparting from the scope and spirit of the invention as defined by theaccompanying claims.

What is claimed is:
 1. A computer-implemented method of identifying andshowing properties matching given criteria based on weights for propertycategories, comprising: causing, by a processor, presentation of agraphical user interface (GUI) on a screen, the GUI including a firstoption that enables specifying a value for a category of a plurality ofcategories associated with a property, a second option that enablesspecifying a weight for the category, and a map; receiving, by theprocessor, a value for the category via the first option and a weightfor the category via the second option; computing a relevance value foreach of a plurality of properties based on the value for the categoryand the weight for the category, the value and the weight in combinationdetermining an amount of contribution of the category to the relevancevalue for the property, including when the property does not match thevalue for the category; causing the map to include a list of visualindicators for one or more properties of the plurality of propertiesbased on locations of the plurality of properties and relevance valuescomputed for the plurality of properties.
 2. The computer-implementedmethod of claim 1, the second option being a slider, an interaction withwhich triggers the computing in real time.
 3. The computer-implementedmethod of claim 1, the computing comprising: increasing the amount ofcontribution of the category when the property matches the value and theweight is relatively large; increasing the amount of contribution of thecategory when the property does not match the value and the weight isrelatively small; decreasing the amount of contribution of the categorywhen the property matches the value and the weight is relatively small;decreasing the amount of contribution of the category when the propertydoes not match the value and the weight is relatively large.
 4. Thecomputer-implemented method of claim 1, the list of visual indicatorsincludes a first group of indicators for exact matches, each being aproperty that matches values specified for the plurality of categoriesand a second group of indicators for non-exact matches, each being aproperty that does not match at least one of the values specified forthe plurality of categories, the first group of indicators and thesecond group of indicators having different appearances.
 5. Thecomputer-implemented method of claim 1, the number of included visualindicators being below a first threshold or the relevance value for eachproperty for which one of the visual indicators is included being abovea second threshold.
 6. The computer-implemented method of claim 1,further comprising receiving a second value for the category or a secondweight for the category, which triggers the computing and the causingthe map to include visual indicators in real time.
 7. Thecomputer-implemented method of claim 1, the GUI further including asection corresponding to a first list of exact matches, each being oneof the plurality of properties that matches values specified for theplurality of categories and a second list of non-exact matches, eachbeing one of the plurality of properties that does not match at leastone of the values specified for the plurality of categories, the sectionhaving values for one or more categories of the plurality of categoriesof each of the first list of exact matches and the second list ofnon-exact matches.
 8. The computer-implemented method of claim 7, thesection having entries for the second list of non-exact matches orderedby relevance values for the non-exact matches.
 9. Thecomputer-implemented method of claim 8, further comprising: receiving aspecific category value via the third option; causing the map to excludefrom the list of visual indicators entries for properties that do nothave the specific category value for the specific category; causing thesection to exclude from the first list of exact matches and the secondlist of non-exact matches entries for properties that do not have thespecific category value for the specific category.
 10. Thecomputer-implemented method of claim 9, the GUI further including athird option for specifying a value for a specific category of the oneor more categories, the third option including a set of category valuesfor the specific category of the first list of exact matches or thesecond list non-exact matches, and for each of the set of categoryvalues, the number of the exact matches or non-exact matches having thecategory value.
 11. One or more non-transitory storage media storinginstructions which, when executed by one or more computing devices,cause performance of a method of identifying and showing propertiesmatching given criteria based on weights for property categories, themethod comprising: causing presentation of a graphical user interface(GUI) on a screen, the GUI including a first option that enablesspecifying a value for a category of a plurality of categoriesassociated with a property, a second option that enables specifying aweight for the category, and a map; receiving a value for the categoryvia the first option and a weight for the category via the secondoption; computing a relevance value for each of a plurality ofproperties based on the value for the category and the weight for thecategory, the value and the weight in combination determining an amountof contribution of the category to the relevance value for the property,including when the property does not match the value for the category;causing the map to include a list of visual indicators for one or moreproperties of the plurality of properties based on locations of theplurality of properties and relevance values computed for the pluralityof properties.
 12. The one or more non-transitory storage media of claim11, the second option being a slider, an interaction with which triggersthe computing in real time.
 13. The one or more non-transitory storagemedia of claim 11, the computing comprising: increasing the amount ofcontribution of the category when the property matches the value and theweight is relatively large; increasing the amount of contribution of thecategory when the property does not match the value and the weight isrelatively small; decreasing the amount of contribution of the categorywhen the property matches the value and the weight is relatively small;decreasing the amount of contribution of the category when the propertydoes not match the value and the weight is relatively large.
 14. The oneor more non-transitory storage media of claim 11, the list of visualindicators includes a first group of indicators for exact matches, eachbeing a property that matches values specified for the plurality ofcategories and a second group of indicators for non-exact matches, eachbeing a property that does not match at least one of the valuesspecified for the plurality of categories, the first group of indicatorsand the second group of indicators having different appearances.
 15. Theone or more non-transitory storage media of claim 11, the number ofincluded visual indicators being below a first threshold or therelevance value for each property for which one of the visual indicatorsis included being above a second threshold.
 16. The one or morenon-transitory storage media of claim 11, the method further comprisingreceiving a second value for the category or a second weight for thecategory, which triggers the computing and the causing the map toinclude visual indicators in real time.
 17. The one or morenon-transitory storage media of claim 11, the GUI further including asection corresponding to a first list of exact matches, each being oneof the plurality of properties that matches values specified for theplurality of categories and a second list of non-exact matches, eachbeing one of the plurality of properties that does not match at leastone of the values specified for the plurality of categories, the sectionhaving values for one or more categories of the plurality of categoriesof each of the first list of exact matches and the second list ofnon-exact matches.
 18. The one or more non-transitory storage media ofclaim 17, the section having entries for the second list of non-exactmatches ordered by relevance values for the non-exact matches.
 19. Theone or more non-transitory storage media of claim 18, the method furthercomprising: receiving a specific category value via the third option;causing the map to exclude from the list of visual indicators entriesfor properties that do not have the specific category value for thespecific category; causing the section to exclude from the first list ofexact matches and the second list of non-exact matches entries forproperties that do not have the specific category value for the specificcategory.
 20. The one or more non-transitory storage media of claim 19,the GUI further including a third option for specifying a value for aspecific category of the one or more categories, the third optionincluding a set of category values for the specific category of thefirst list of exact matches or the second list non-exact matches, andfor each of the set of category values, the number of the exact matchesor non-exact matches having the category value.